From 46c392b2982dcaad189361e6d10c1ab62bb94d6f Mon Sep 17 00:00:00 2001 From: Lev Date: Thu, 1 Jun 2023 10:00:44 +0300 Subject: [PATCH] 404 fixes (#311) --- ...21-12-24-sbiobertresolve_loinc_cased_en.md | 2 +- ...04-02-chunkresolve_icd10pcs_clinical_en.md | 2 +- ...4-16-chunkresolve_rxnorm_cd_clinical_en.md | 2 +- ...-16-chunkresolve_rxnorm_sbd_clinical_en.md | 2 +- ...-16-chunkresolve_rxnorm_scd_clinical_en.md | 2 +- ...-chunkresolve_rxnorm_xsmall_clinical_en.md | 2 +- ...hunkresolve_snomed_findings_clinical_en.md | 2 +- .../2021-04-29-sbluebertresolve_loinc_en.md | 2 +- .../2021-05-16-sbiobertresolve_cpt_en.md | 2 +- ...solve_icd10cm_augmented_billable_hcc_en.md | 2 +- .../2021-05-16-sbiobertresolve_icd10cm_en.md | 2 +- .../2021-05-16-sbiobertresolve_icd10pcs_en.md | 2 +- .../2021-05-16-sbiobertresolve_icdo_en.md | 2 +- .../2021-05-16-sbiobertresolve_rxcui_en.md | 2 +- ...6-sbiobertresolve_snomed_auxConcepts_en.md | 2 +- ...iobertresolve_snomed_auxConcepts_int_en.md | 2 +- 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2 +- .../2022-09-06-finclf_bert_fls_en.md | 2 +- ...2-09-27-legner_bert_indemnifications_en.md | 2 +- .../2022-09-28-finre_work_experience_en.md | 4 +- .../2022-09-28-legre_indemnifications_en.md | 2 +- .../2022-11-08-finre_work_experience_md_en.md | 4 +- .../2022-11-09-legner_termination_en.md | 2 +- ...12-01-legner_contract_doc_parties_md_en.md | 2 +- ...022-12-01-legner_indemnifications_md_en.md | 2 +- .../2022-12-01-legner_termination_md_en.md | 2 +- .../2022-12-01-legner_warranty_md_en.md | 2 +- .../2022-12-01-legner_whereas_md_en.md | 2 +- ...01-21-legner_contract_doc_parties_lg_en.md | 2 +- ...021-10-05-sbiobertresolve_rxnorm_ndc_en.md | 2 +- .../demos/databricks_solution_accelerators.md | 17 +++-- .../release_notes_2_8_0.md | 2 +- .../release_notes_3_0_0.md | 8 +-- docs/en/alab/project_creation.md | 20 ++++-- docs/en/display.md | 2 +- docs/en/jsl/jsl_release_notes.md | 62 +++++++++---------- docs/en/jsl/release_notes.md | 20 +++--- 75 files changed, 141 insertions(+), 132 deletions(-) diff --git a/docs/_posts/Ahmetemintek/2021-12-24-sbiobertresolve_loinc_cased_en.md b/docs/_posts/Ahmetemintek/2021-12-24-sbiobertresolve_loinc_cased_en.md index 73289bfa26..4d89797bf8 100644 --- a/docs/_posts/Ahmetemintek/2021-12-24-sbiobertresolve_loinc_cased_en.md +++ b/docs/_posts/Ahmetemintek/2021-12-24-sbiobertresolve_loinc_cased_en.md @@ -26,7 +26,7 @@ This model maps extracted clinical NER entities to LOINC codes using `sbiobert_b `LOINC` {:.btn-box} -[Live Demo](https://demo.johnsnowlabs.com/healthcare/ER_LOINC_AUGMENTED/){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/24.Improved_Entity_Resolvers_in_SparkNLP_with_sBert.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_loinc_cased_en_3.3.4_2.4_1640374998947.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_loinc_cased_en_3.3.4_2.4_1640374998947.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-04-02-chunkresolve_icd10pcs_clinical_en.md b/docs/_posts/HashamUlHaq/2021-04-02-chunkresolve_icd10pcs_clinical_en.md index a0849a9bd3..0f40090dc9 100644 --- a/docs/_posts/HashamUlHaq/2021-04-02-chunkresolve_icd10pcs_clinical_en.md +++ b/docs/_posts/HashamUlHaq/2021-04-02-chunkresolve_icd10pcs_clinical_en.md @@ -26,7 +26,7 @@ Entity Resolution model Based on KNN using Word Embeddings + Word Movers Distanc ICD10-PCS Codes and their normalized definition with `clinical_embeddings`. {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/chunkresolve_icd10pcs_clinical_en_3.0.0_3.0_1617355415038.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/chunkresolve_icd10pcs_clinical_en_3.0.0_3.0_1617355415038.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-04-16-chunkresolve_rxnorm_cd_clinical_en.md b/docs/_posts/HashamUlHaq/2021-04-16-chunkresolve_rxnorm_cd_clinical_en.md index ea4d08474b..f03345a224 100644 --- a/docs/_posts/HashamUlHaq/2021-04-16-chunkresolve_rxnorm_cd_clinical_en.md +++ b/docs/_posts/HashamUlHaq/2021-04-16-chunkresolve_rxnorm_cd_clinical_en.md @@ -26,7 +26,7 @@ Entity Resolution model Based on KNN using Word Embeddings + Word Movers Distanc RxNorm Codes and their normalized definition with `clinical_embeddings`. {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/chunkresolve_rxnorm_cd_clinical_en_3.0.0_3.0_1618603400196.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/chunkresolve_rxnorm_cd_clinical_en_3.0.0_3.0_1618603400196.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-04-16-chunkresolve_rxnorm_sbd_clinical_en.md b/docs/_posts/HashamUlHaq/2021-04-16-chunkresolve_rxnorm_sbd_clinical_en.md index 3175249939..f36c1b4362 100644 --- a/docs/_posts/HashamUlHaq/2021-04-16-chunkresolve_rxnorm_sbd_clinical_en.md +++ b/docs/_posts/HashamUlHaq/2021-04-16-chunkresolve_rxnorm_sbd_clinical_en.md @@ -26,7 +26,7 @@ Entity Resolution model Based on KNN using Word Embeddings + Word Movers Distanc RxNorm Codes and their normalized definition with `clinical_embeddings`. {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/chunkresolve_rxnorm_sbd_clinical_en_3.0.0_3.0_1618603306546.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/chunkresolve_rxnorm_sbd_clinical_en_3.0.0_3.0_1618603306546.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-04-16-chunkresolve_rxnorm_scd_clinical_en.md b/docs/_posts/HashamUlHaq/2021-04-16-chunkresolve_rxnorm_scd_clinical_en.md index 77c9770d3f..bbd197c6d1 100644 --- a/docs/_posts/HashamUlHaq/2021-04-16-chunkresolve_rxnorm_scd_clinical_en.md +++ b/docs/_posts/HashamUlHaq/2021-04-16-chunkresolve_rxnorm_scd_clinical_en.md @@ -26,7 +26,7 @@ Entity Resolution model Based on KNN using Word Embeddings + Word Movers Distanc RxNorm Codes and their normalized definition with `clinical_embeddings`. {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/chunkresolve_rxnorm_scd_clinical_en_3.0.0_3.0_1618603397185.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/chunkresolve_rxnorm_scd_clinical_en_3.0.0_3.0_1618603397185.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-04-16-chunkresolve_rxnorm_xsmall_clinical_en.md b/docs/_posts/HashamUlHaq/2021-04-16-chunkresolve_rxnorm_xsmall_clinical_en.md index 57febffa28..81d7fd8fe7 100644 --- a/docs/_posts/HashamUlHaq/2021-04-16-chunkresolve_rxnorm_xsmall_clinical_en.md +++ b/docs/_posts/HashamUlHaq/2021-04-16-chunkresolve_rxnorm_xsmall_clinical_en.md @@ -26,7 +26,7 @@ Entity Resolution model Based on KNN using Word Embeddings + Word Movers Distanc RxNorm Codes and their normalized definition with `clinical_embeddings`. {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/chunkresolve_rxnorm_xsmall_clinical_en_3.0.0_3.0_1618603394135.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/chunkresolve_rxnorm_xsmall_clinical_en_3.0.0_3.0_1618603394135.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-04-16-chunkresolve_snomed_findings_clinical_en.md b/docs/_posts/HashamUlHaq/2021-04-16-chunkresolve_snomed_findings_clinical_en.md index 2c7312163e..a1587cd24d 100644 --- a/docs/_posts/HashamUlHaq/2021-04-16-chunkresolve_snomed_findings_clinical_en.md +++ b/docs/_posts/HashamUlHaq/2021-04-16-chunkresolve_snomed_findings_clinical_en.md @@ -26,7 +26,7 @@ Entity Resolution model Based on KNN using Word Embeddings + Word Movers Distanc Snomed Codes and their normalized definition with `clinical_embeddings`. {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/chunkresolve_snomed_findings_clinical_en_3.0.0_3.0_1618603404974.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/chunkresolve_snomed_findings_clinical_en_3.0.0_3.0_1618603404974.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-04-29-sbluebertresolve_loinc_en.md b/docs/_posts/HashamUlHaq/2021-04-29-sbluebertresolve_loinc_en.md index 1e4589c7a6..9a87332a88 100644 --- a/docs/_posts/HashamUlHaq/2021-04-29-sbluebertresolve_loinc_en.md +++ b/docs/_posts/HashamUlHaq/2021-04-29-sbluebertresolve_loinc_en.md @@ -26,7 +26,7 @@ Map clinical NER entities to LOINC codes. LOINC codes - per input NER entity {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/24.Improved_Entity_Resolvers_in_SparkNLP_with_sBert.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbluebertresolve_loinc_en_3.0.2_3.0_1619678534366.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbluebertresolve_loinc_en_3.0.2_3.0_1619678534366.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_cpt_en.md b/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_cpt_en.md index f9e16897c6..8b2cf514a8 100644 --- a/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_cpt_en.md +++ b/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_cpt_en.md @@ -26,7 +26,7 @@ This model maps extracted medical entities to CPT codes using `sbiobert_base_cas Predicts CPT codes and their descriptions. {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_cpt_en_3.0.4_3.0_1621189492240.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_cpt_en_3.0.4_3.0_1621189492240.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_icd10cm_augmented_billable_hcc_en.md b/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_icd10cm_augmented_billable_hcc_en.md index 1a296c1fe7..c495a4c0c4 100644 --- a/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_icd10cm_augmented_billable_hcc_en.md +++ b/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_icd10cm_augmented_billable_hcc_en.md @@ -26,7 +26,7 @@ This model maps extracted medical entities to ICD10-CM codes using `sbiobert_bas Outputs 7-digit billable ICD codes. In the result, look for `aux_label` parameter in the metadata to get HCC status. The HCC status can be divided to get further information: `billable status`, `hcc status`, and `hcc score`.For example, in the example shared `below the billable status is 1`, `hcc status is 1`, and `hcc score is 8`. {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_icd10cm_augmented_billable_hcc_en_3.0.4_2.4_1621189647111.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_icd10cm_augmented_billable_hcc_en_3.0.4_2.4_1621189647111.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_icd10cm_en.md b/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_icd10cm_en.md index 76156f1639..be8b5a60ae 100644 --- a/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_icd10cm_en.md +++ b/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_icd10cm_en.md @@ -26,7 +26,7 @@ This model maps extracted medical entities to ICD10-CM codes using `sbiobert_bas Predicts ICD10-CM Codes and their normalized definitions. {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_icd10cm_en_3.0.4_3.0_1621189196513.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_icd10cm_en_3.0.4_3.0_1621189196513.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_icd10pcs_en.md b/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_icd10pcs_en.md index 777e4a6d4f..5a51475877 100644 --- a/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_icd10pcs_en.md +++ b/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_icd10pcs_en.md @@ -26,7 +26,7 @@ This model maps extracted medical entities to ICD10-PCS codes using `sbiobert_ba Predicts ICD10-PCS Codes and their normalized definitions. {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_icd10pcs_en_3.0.4_3.0_1621189710474.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_icd10pcs_en_3.0.4_3.0_1621189710474.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_icdo_en.md b/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_icdo_en.md index 6930309897..5eb59fd9b1 100644 --- a/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_icdo_en.md +++ b/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_icdo_en.md @@ -28,7 +28,7 @@ Given an oncological entity found in the text (via NER models like ner_jsl), it Predicts ICD-O Codes and their normalized definition for each chunk. {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_icdo_en_3.0.4_3.0_1621191532225.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_icdo_en_3.0.4_3.0_1621191532225.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_rxcui_en.md b/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_rxcui_en.md index 535dfd0a71..c7d3360932 100644 --- a/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_rxcui_en.md +++ b/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_rxcui_en.md @@ -26,7 +26,7 @@ This model maps clinical entities and concepts (like drugs/ingredients) to RxCUI Predicts RxCUI Codes and their normalized definition for each chunk. {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_rxcui_en_3.0.4_3.0_1621189488426.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_rxcui_en_3.0.4_3.0_1621189488426.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_snomed_auxConcepts_en.md b/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_snomed_auxConcepts_en.md index e6ccb7bce5..80cf8c9090 100644 --- a/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_snomed_auxConcepts_en.md +++ b/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_snomed_auxConcepts_en.md @@ -29,7 +29,7 @@ It has faster load time, with a speedup of about 6X when compared to previous ve Predicts Snomed Codes and their normalized definition for each chunk. {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_snomed_auxConcepts_en_3.0.4_3.0_1621189567327.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_snomed_auxConcepts_en_3.0.4_3.0_1621189567327.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_snomed_auxConcepts_int_en.md b/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_snomed_auxConcepts_int_en.md index 15781e5d00..cf5c7b7e6f 100644 --- a/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_snomed_auxConcepts_int_en.md +++ b/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_snomed_auxConcepts_int_en.md @@ -29,7 +29,7 @@ It has faster load time, with a speedup of about 6X when compared to previous ve Predicts Snomed Codes and their normalized definition for each chunk. {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_snomed_auxConcepts_int_en_3.0.4_3.0_1621191454309.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_snomed_auxConcepts_int_en_3.0.4_3.0_1621191454309.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_snomed_findings_en.md b/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_snomed_findings_en.md index efd392503e..a62cb1288c 100644 --- a/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_snomed_findings_en.md +++ b/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_snomed_findings_en.md @@ -26,7 +26,7 @@ This model maps extracted medical entities to Snomed codes (CT version) using `s Predicts Snomed Codes and their normalized definition for each chunk. {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_snomed_findings_en_3.0.4_3.0_1621191323188.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_snomed_findings_en_3.0.4_3.0_1621191323188.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_snomed_findings_int_en.md b/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_snomed_findings_int_en.md index 80abf64a8e..9fa8b39155 100644 --- a/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_snomed_findings_int_en.md +++ b/docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_snomed_findings_int_en.md @@ -26,7 +26,7 @@ This model maps extracted medical entities to Snomed codes (INT version) using u Predicts Snomed Codes and their normalized definition for each chunk. {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_snomed_findings_int_en_3.0.4_3.0_1621189624936.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_snomed_findings_int_en_3.0.4_3.0_1621189624936.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-05-21-sbertresolve_icd10cm_slim_billable_hcc_med_en.md b/docs/_posts/HashamUlHaq/2021-05-21-sbertresolve_icd10cm_slim_billable_hcc_med_en.md index a9dc4853f5..0c234c219f 100644 --- a/docs/_posts/HashamUlHaq/2021-05-21-sbertresolve_icd10cm_slim_billable_hcc_med_en.md +++ b/docs/_posts/HashamUlHaq/2021-05-21-sbertresolve_icd10cm_slim_billable_hcc_med_en.md @@ -25,7 +25,7 @@ This model maps extracted medical entities to ICD10-CM codes using sentence embe Outputs 7-digit billable ICD codes. In the result, look for aux_label parameter in the metadata to get HCC status. The HCC status can be divided to get further information: billable status, hcc status, and hcc score. {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/24.Improved_Entity_Resolvers_in_SparkNLP_with_sBert.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbertresolve_icd10cm_slim_billable_hcc_med_en_3.0.4_2.4_1621590174924.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbertresolve_icd10cm_slim_billable_hcc_med_en_3.0.4_2.4_1621590174924.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-05-30-sbiobertresolve_cpt_augmented_en.md b/docs/_posts/HashamUlHaq/2021-05-30-sbiobertresolve_cpt_augmented_en.md index c8885b3731..de041ae760 100644 --- a/docs/_posts/HashamUlHaq/2021-05-30-sbiobertresolve_cpt_augmented_en.md +++ b/docs/_posts/HashamUlHaq/2021-05-30-sbiobertresolve_cpt_augmented_en.md @@ -26,7 +26,7 @@ This model maps extracted medical entities to CPT codes using `sbiobert_base_cas CPT codes and their descriptions. {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/24.Improved_Entity_Resolvers_in_SparkNLP_with_sBert.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_cpt_augmented_en_3.0.4_3.0_1622372290384.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_cpt_augmented_en_3.0.4_3.0_1622372290384.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-05-30-sbiobertresolve_cpt_procedures_augmented_en.md b/docs/_posts/HashamUlHaq/2021-05-30-sbiobertresolve_cpt_procedures_augmented_en.md index 0509819435..26491ab5f7 100644 --- a/docs/_posts/HashamUlHaq/2021-05-30-sbiobertresolve_cpt_procedures_augmented_en.md +++ b/docs/_posts/HashamUlHaq/2021-05-30-sbiobertresolve_cpt_procedures_augmented_en.md @@ -26,7 +26,7 @@ This model maps extracted medical entities to CPT codes using `sbiobert_base_cas CPT codes and their descriptions. {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/24.Improved_Entity_Resolvers_in_SparkNLP_with_sBert.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_cpt_procedures_augmented_en_3.0.4_3.0_1622371775342.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_cpt_procedures_augmented_en_3.0.4_3.0_1622371775342.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-05-30-sbiobertresolve_hcc_augmented_en.md b/docs/_posts/HashamUlHaq/2021-05-30-sbiobertresolve_hcc_augmented_en.md index 026e6b2150..bf448fa20c 100644 --- a/docs/_posts/HashamUlHaq/2021-05-30-sbiobertresolve_hcc_augmented_en.md +++ b/docs/_posts/HashamUlHaq/2021-05-30-sbiobertresolve_hcc_augmented_en.md @@ -26,7 +26,7 @@ This model maps extracted medical entities to HCC codes using Sentence Bert Embe HCC codes and their descriptions. {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/24.Improved_Entity_Resolvers_in_SparkNLP_with_sBert.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_hcc_augmented_en_3.0.4_3.0_1622370690651.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_hcc_augmented_en_3.0.4_3.0_1622370690651.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-06-30-sbert_jsl_medium_umls_uncased_en.md b/docs/_posts/HashamUlHaq/2021-06-30-sbert_jsl_medium_umls_uncased_en.md index 4b344ac231..3f7b137da9 100644 --- a/docs/_posts/HashamUlHaq/2021-06-30-sbert_jsl_medium_umls_uncased_en.md +++ b/docs/_posts/HashamUlHaq/2021-06-30-sbert_jsl_medium_umls_uncased_en.md @@ -25,7 +25,7 @@ This model is trained to generate contextual sentence embeddings of input senten {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbert_jsl_medium_umls_uncased_en_3.1.0_2.4_1625050119656.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbert_jsl_medium_umls_uncased_en_3.1.0_2.4_1625050119656.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-06-30-sbert_jsl_medium_uncased_en.md b/docs/_posts/HashamUlHaq/2021-06-30-sbert_jsl_medium_uncased_en.md index dd183a80e4..e89d07fa4d 100644 --- a/docs/_posts/HashamUlHaq/2021-06-30-sbert_jsl_medium_uncased_en.md +++ b/docs/_posts/HashamUlHaq/2021-06-30-sbert_jsl_medium_uncased_en.md @@ -25,7 +25,7 @@ This model is trained to generate contextual sentence embeddings of input senten {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbert_jsl_medium_uncased_en_3.1.0_2.4_1625050209626.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbert_jsl_medium_uncased_en_3.1.0_2.4_1625050209626.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-06-30-sbert_jsl_mini_umls_uncased_en.md b/docs/_posts/HashamUlHaq/2021-06-30-sbert_jsl_mini_umls_uncased_en.md index c4bba0cb51..c7bb63b5e2 100644 --- a/docs/_posts/HashamUlHaq/2021-06-30-sbert_jsl_mini_umls_uncased_en.md +++ b/docs/_posts/HashamUlHaq/2021-06-30-sbert_jsl_mini_umls_uncased_en.md @@ -25,7 +25,7 @@ This model is trained to generate contextual sentence embeddings of input senten {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbert_jsl_mini_umls_uncased_en_3.1.0_2.4_1625050218116.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbert_jsl_mini_umls_uncased_en_3.1.0_2.4_1625050218116.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-06-30-sbert_jsl_mini_uncased_en.md b/docs/_posts/HashamUlHaq/2021-06-30-sbert_jsl_mini_uncased_en.md index 36f106a238..4aa2ff95e0 100644 --- a/docs/_posts/HashamUlHaq/2021-06-30-sbert_jsl_mini_uncased_en.md +++ b/docs/_posts/HashamUlHaq/2021-06-30-sbert_jsl_mini_uncased_en.md @@ -25,7 +25,7 @@ This model is trained to generate contextual sentence embeddings of input senten {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbert_jsl_mini_uncased_en_3.1.0_2.4_1625050221194.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbert_jsl_mini_uncased_en_3.1.0_2.4_1625050221194.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-06-30-sbert_jsl_tiny_umls_uncased_en.md b/docs/_posts/HashamUlHaq/2021-06-30-sbert_jsl_tiny_umls_uncased_en.md index a8d59ed78f..fe6e21b029 100644 --- a/docs/_posts/HashamUlHaq/2021-06-30-sbert_jsl_tiny_umls_uncased_en.md +++ b/docs/_posts/HashamUlHaq/2021-06-30-sbert_jsl_tiny_umls_uncased_en.md @@ -25,7 +25,7 @@ This model is trained to generate contextual sentence embeddings of input senten {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbert_jsl_tiny_umls_uncased_en_3.1.0_2.4_1625050224767.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbert_jsl_tiny_umls_uncased_en_3.1.0_2.4_1625050224767.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-06-30-sbert_jsl_tiny_uncased_en.md b/docs/_posts/HashamUlHaq/2021-06-30-sbert_jsl_tiny_uncased_en.md index 4364a345ca..6d8df8a5c5 100644 --- a/docs/_posts/HashamUlHaq/2021-06-30-sbert_jsl_tiny_uncased_en.md +++ b/docs/_posts/HashamUlHaq/2021-06-30-sbert_jsl_tiny_uncased_en.md @@ -25,7 +25,7 @@ This model is trained to generate contextual sentence embeddings of input senten {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbert_jsl_tiny_uncased_en_3.1.0_2.4_1625050227188.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbert_jsl_tiny_uncased_en_3.1.0_2.4_1625050227188.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-06-30-sbiobert_jsl_cased_en.md b/docs/_posts/HashamUlHaq/2021-06-30-sbiobert_jsl_cased_en.md index 72b2174ae7..9c86cdec4f 100644 --- a/docs/_posts/HashamUlHaq/2021-06-30-sbiobert_jsl_cased_en.md +++ b/docs/_posts/HashamUlHaq/2021-06-30-sbiobert_jsl_cased_en.md @@ -25,7 +25,7 @@ This model is trained to generate contextual sentence embeddings of input senten {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobert_jsl_cased_en_3.1.0_2.4_1625050229429.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobert_jsl_cased_en_3.1.0_2.4_1625050229429.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-06-30-sbiobert_jsl_umls_cased_en.md b/docs/_posts/HashamUlHaq/2021-06-30-sbiobert_jsl_umls_cased_en.md index 2cd4d9b043..3f6d04ea15 100644 --- a/docs/_posts/HashamUlHaq/2021-06-30-sbiobert_jsl_umls_cased_en.md +++ b/docs/_posts/HashamUlHaq/2021-06-30-sbiobert_jsl_umls_cased_en.md @@ -25,7 +25,7 @@ This model is trained to generate contextual sentence embeddings of input senten {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobert_jsl_umls_cased_en_3.1.0_2.4_1625050246280.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobert_jsl_umls_cased_en_3.1.0_2.4_1625050246280.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/HashamUlHaq/2021-09-01-ner_posology_experimental_en.md b/docs/_posts/HashamUlHaq/2021-09-01-ner_posology_experimental_en.md index c9326c6809..a9f23185c6 100644 --- a/docs/_posts/HashamUlHaq/2021-09-01-ner_posology_experimental_en.md +++ b/docs/_posts/HashamUlHaq/2021-09-01-ner_posology_experimental_en.md @@ -31,7 +31,7 @@ This model detects drugs, experimental drugs, cyclelength, cyclecount, cycledaty {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/1.Clinical_Named_Entity_Recognition_Model.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/ner_posology_experimental_en_3.1.3_3.0_1630511369574.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/ner_posology_experimental_en_3.1.3_3.0_1630511369574.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/aymanechilah/2023-01-10-visualner_10kfilings_en_3_2.md b/docs/_posts/aymanechilah/2023-01-10-visualner_10kfilings_en_3_2.md index e8cf1d9753..9a3f32abaf 100644 --- a/docs/_posts/aymanechilah/2023-01-10-visualner_10kfilings_en_3_2.md +++ b/docs/_posts/aymanechilah/2023-01-10-visualner_10kfilings_en_3_2.md @@ -26,7 +26,7 @@ This model is a Visual NER team aimed to extract the main key points in the summ `REGISTRANT`, `ADDRESS`, `PHONE`, `DATE`, `EMPLOYERIDNB`, `EXCHANGE`, `STATE`, `STOCKCLASS`, `STOCKVALUE`, `TRADINGSYMBOL`, `FILENUMBER` {:.btn-box} -[Live Demo](https://demo.johnsnowlabs.com/ocr/VISUAL_DOCUMENT_KEYVALUES_NER/){:.button.button-orange.button-orange-trans.co.button-icon} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange.button-orange-trans.co.button-icon} [Open in Colab](https://github.com/JohnSnowLabs/spark-nlp-workshop/blob/master/finance-nlp/90.2.Financial_Visual_NER.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/ocr/visualner_10kfilings_en_4.0.0_3.2_1663769328577.zip){:.button.button-orange.button-orange-trans.arr.button-icon} diff --git a/docs/_posts/aymanechilah/2023-01-10-visualner_keyvalue_10kfilings_en_3_2.md b/docs/_posts/aymanechilah/2023-01-10-visualner_keyvalue_10kfilings_en_3_2.md index cb662a1ef5..acac882b4e 100644 --- a/docs/_posts/aymanechilah/2023-01-10-visualner_keyvalue_10kfilings_en_3_2.md +++ b/docs/_posts/aymanechilah/2023-01-10-visualner_keyvalue_10kfilings_en_3_2.md @@ -26,7 +26,7 @@ This is a Form Recognition / Key Value extraction model, trained on the summary `KEY`, `VALUE`, `HEADER` {:.btn-box} -[Live Demo](https://demo.johnsnowlabs.com/ocr/VISUAL_DOCUMENT_KEYVALUES_NER/){:.button.button-orange.button-orange-trans.co.button-icon} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange.button-orange-trans.co.button-icon} [Open in Colab](https://github.com/JohnSnowLabs/spark-nlp-workshop/blob/master/finance-nlp/90.2.Financial_Visual_NER.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/ocr/visualner_keyvalue_10kfilings_en_4.0.0_3.2_1663781115795.zip){:.button.button-orange.button-orange-trans.arr.button-icon} diff --git a/docs/_posts/bunyamin-polat/2022-11-02-legre_contract_doc_parties_md_en.md b/docs/_posts/bunyamin-polat/2022-11-02-legre_contract_doc_parties_md_en.md index 1cbf80b01e..63bb142b13 100644 --- a/docs/_posts/bunyamin-polat/2022-11-02-legre_contract_doc_parties_md_en.md +++ b/docs/_posts/bunyamin-polat/2022-11-02-legre_contract_doc_parties_md_en.md @@ -19,7 +19,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_introduction_clause` Text Classifier to select only these paragraphs; - This is a Legal Relation Extraction model, which can be used after the NER Model for extracting Parties, Document Types, Effective Dates and Aliases, called legner_contract_doc_parties. diff --git a/docs/_posts/bunyamin-polat/2022-11-03-legre_obligations_md_en.md b/docs/_posts/bunyamin-polat/2022-11-03-legre_obligations_md_en.md index 433f5ba22c..03d1454d5b 100644 --- a/docs/_posts/bunyamin-polat/2022-11-03-legre_obligations_md_en.md +++ b/docs/_posts/bunyamin-polat/2022-11-03-legre_obligations_md_en.md @@ -19,7 +19,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_cuad_obligations_clause` Text Classifier to select only these paragraphs; We call "obligation" to any sentence in the text stating that a Party (OBLIGATION_SUBJECT) must do (OBLIGATION_ACITON) something (OBLIGATION_OBJECT) to other Party (OBLIGATION_INDIRECT_OBJECT). This model extracts relationships, connecting all of those parts of the sentence (subject with action, action with object, etc). diff --git a/docs/_posts/egenc/2022-01-18-sbiobertresolve_loinc_augmented_en.md b/docs/_posts/egenc/2022-01-18-sbiobertresolve_loinc_augmented_en.md index 16d9835fdc..5b1060dcf7 100644 --- a/docs/_posts/egenc/2022-01-18-sbiobertresolve_loinc_augmented_en.md +++ b/docs/_posts/egenc/2022-01-18-sbiobertresolve_loinc_augmented_en.md @@ -26,7 +26,7 @@ This model maps extracted clinical NER entities to LOINC codes using `sbiobert_b {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/24.Improved_Entity_Resolvers_in_SparkNLP_with_sBert.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_loinc_augmented_en_3.3.2_2.4_1642533239691.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_loinc_augmented_en_3.3.2_2.4_1642533239691.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/egenc/2022-01-18-sbluebertresolve_loinc_uncased_en.md b/docs/_posts/egenc/2022-01-18-sbluebertresolve_loinc_uncased_en.md index 4433bf822d..57ccd04f02 100644 --- a/docs/_posts/egenc/2022-01-18-sbluebertresolve_loinc_uncased_en.md +++ b/docs/_posts/egenc/2022-01-18-sbluebertresolve_loinc_uncased_en.md @@ -26,7 +26,7 @@ This model maps extracted clinical NER entities to LOINC codes using `sbluebert_ `LOINC Code` {:.btn-box} -[Live Demo](https://demo.johnsnowlabs.com/healthcare/ER_LOINC_AUGMENTED/){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/24.Improved_Entity_Resolvers_in_SparkNLP_with_sBert.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbluebertresolve_loinc_uncased_en_3.3.4_2.4_1642535076764.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbluebertresolve_loinc_uncased_en_3.3.4_2.4_1642535076764.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/gadde5300/2022-10-17-legner_confidentiality_en.md b/docs/_posts/gadde5300/2022-10-17-legner_confidentiality_en.md index 8d79ba0585..4bad6da756 100644 --- a/docs/_posts/gadde5300/2022-10-17-legner_confidentiality_en.md +++ b/docs/_posts/gadde5300/2022-10-17-legner_confidentiality_en.md @@ -19,7 +19,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_cuad_confidentiality_clause` Text Classifier to select only these paragraphs; This is a Legal Named Entity Recognition Model to identify the Subject (who), Action (web), Object(the indemnification) and Indirect Object (to whom) from Confidentiality clauses. diff --git a/docs/_posts/gadde5300/2022-10-17-legner_warranty_en.md b/docs/_posts/gadde5300/2022-10-17-legner_warranty_en.md index 1469874a0e..cc2e25e37a 100644 --- a/docs/_posts/gadde5300/2022-10-17-legner_warranty_en.md +++ b/docs/_posts/gadde5300/2022-10-17-legner_warranty_en.md @@ -19,7 +19,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_warranty_clause` Text Classifier to select only these paragraphs; This is a Legal Named Entity Recognition Model to identify the Subject (who), Action (what), Object(the indemnification) and Indirect Object (to whom) from Warranty clauses. diff --git a/docs/_posts/gadde5300/2022-10-18-legre_confidentiality_en.md b/docs/_posts/gadde5300/2022-10-18-legre_confidentiality_en.md index 19a7a08413..33e4e73eac 100644 --- a/docs/_posts/gadde5300/2022-10-18-legre_confidentiality_en.md +++ b/docs/_posts/gadde5300/2022-10-18-legre_confidentiality_en.md @@ -19,7 +19,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_cuad_confidentiality_clause` Text Classifier to select only these paragraphs; This is a Legal Relation Extraction Model to identify the Subject (who), Action (web), Object(the indemnification) and Indirect Object (to whom) from confidentiality clauses. diff --git a/docs/_posts/gadde5300/2022-10-19-legre_warranty_en.md b/docs/_posts/gadde5300/2022-10-19-legre_warranty_en.md index 6be29e887c..eb0418f1aa 100644 --- a/docs/_posts/gadde5300/2022-10-19-legre_warranty_en.md +++ b/docs/_posts/gadde5300/2022-10-19-legre_warranty_en.md @@ -19,7 +19,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_warranty_clause` Text Classifier to select only these paragraphs; This is a Legal Relation Extraction Model to identify the Subject (who), Action (web), Object(the indemnification) and Indirect Object (to whom) from warranty clauses. diff --git a/docs/_posts/gadde5300/2022-11-09-legre_confidentiality_md_en.md b/docs/_posts/gadde5300/2022-11-09-legre_confidentiality_md_en.md index 2f0ea082ef..3443aa43db 100644 --- a/docs/_posts/gadde5300/2022-11-09-legre_confidentiality_md_en.md +++ b/docs/_posts/gadde5300/2022-11-09-legre_confidentiality_md_en.md @@ -19,7 +19,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_cuad_confidentiality_clause` Text Classifier to select only these paragraphs; This is a Legal Relation Extraction Model to identify the Subject (who), Action (what), Object(the confidentiality) and Indirect Object (to whom) from confidentiality clauses. This model requires `legner_confidentiality` as an NER in the pipeline. It's a `md` model with Unidirectional Relations, meaning that the model retrieves in chunk1 the left side of the relation (source), and in chunk2 the right side (target). diff --git a/docs/_posts/gadde5300/2022-11-09-legre_indemnifications_md_en.md b/docs/_posts/gadde5300/2022-11-09-legre_indemnifications_md_en.md index dd37313b18..c2ed9e71b6 100644 --- a/docs/_posts/gadde5300/2022-11-09-legre_indemnifications_md_en.md +++ b/docs/_posts/gadde5300/2022-11-09-legre_indemnifications_md_en.md @@ -19,7 +19,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_indemnification_clause` Text Classifier to select only these paragraphs; This is a Relation Extraction model to group the different entities extracted with the Indemnification NER model (see `legner_bert_indemnifications` in Models Hub). This model requires `legner_bert_indemnifications` as an NER in the pipeline. It's a `md` model with Unidirectional Relations, meaning that the model retrieves in chunk1 the left side of the relation (source), and in chunk2 the right side (target). diff --git a/docs/_posts/gadde5300/2022-11-09-legre_whereas_md_en.md b/docs/_posts/gadde5300/2022-11-09-legre_whereas_md_en.md index 4f0d532de9..80d47ff769 100644 --- a/docs/_posts/gadde5300/2022-11-09-legre_whereas_md_en.md +++ b/docs/_posts/gadde5300/2022-11-09-legre_whereas_md_en.md @@ -19,7 +19,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_cuad_wheras_clause` Text Classifier to select only these paragraphs; This is a Relation Extraction model to infer relations between elements in WHEREAS clauses, more specifically the SUBJECT, the ACTION and the OBJECT. There are two relations possible: `has_subject` and `has_object`. You can also use `legpipe_whereas` which includes this model and its NER and also depedency parsing, to carry out chunk extraction using grammatical features (the dependency tree). This model requires `legner_whereas` as an NER in the pipeline. It's a `md` model with Unidirectional Relations, meaning that the model retrieves in chunk1 the left side of the relation (source), and in chunk2 the right side (target). diff --git a/docs/_posts/gadde5300/2023-02-02-legpipe_ner_contract_doc_parties_alias_former_en.md b/docs/_posts/gadde5300/2023-02-02-legpipe_ner_contract_doc_parties_alias_former_en.md index 4c7f17af62..0d84f7e25d 100644 --- a/docs/_posts/gadde5300/2023-02-02-legpipe_ner_contract_doc_parties_alias_former_en.md +++ b/docs/_posts/gadde5300/2023-02-02-legpipe_ner_contract_doc_parties_alias_former_en.md @@ -21,7 +21,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this pretrained pipeline on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_introduction_clause` Text Classifier to select only these paragraphs; This is a Legal NER Pipeline, aimed to process the first page of the agreements when information can be found about: diff --git a/docs/_posts/gadde5300/2023-02-17-legre_contract_doc_parties_lg_en.md b/docs/_posts/gadde5300/2023-02-17-legre_contract_doc_parties_lg_en.md index 3954c7d84c..6dbf1a5ea2 100644 --- a/docs/_posts/gadde5300/2023-02-17-legre_contract_doc_parties_lg_en.md +++ b/docs/_posts/gadde5300/2023-02-17-legre_contract_doc_parties_lg_en.md @@ -21,7 +21,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_introduction_clause` Text Classifier to select only these paragraphs; - This is a Legal Relation Extraction model, which can be used after the NER Model for extracting Parties, Document Types, Effective Dates and Aliases, called legner_contract_doc_parties. diff --git a/docs/_posts/iamvarol/2021-11-23-sbiobertresolve_loinc_augmented_en.md b/docs/_posts/iamvarol/2021-11-23-sbiobertresolve_loinc_augmented_en.md index 9c55a34473..a2a0714565 100644 --- a/docs/_posts/iamvarol/2021-11-23-sbiobertresolve_loinc_augmented_en.md +++ b/docs/_posts/iamvarol/2021-11-23-sbiobertresolve_loinc_augmented_en.md @@ -25,7 +25,7 @@ This model maps extracted clinical NER entities to LOINC codes using `sbiobert_b {:.btn-box} -[Live Demo](https://nlp.johnsnowlabs.com/demo){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/24.Improved_Entity_Resolvers_in_SparkNLP_with_sBert.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_loinc_augmented_en_3.3.2_2.4_1637664939262.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_loinc_augmented_en_3.3.2_2.4_1637664939262.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/iamvarol/2021-12-31-sbluebertresolve_loinc_uncased_en.md b/docs/_posts/iamvarol/2021-12-31-sbluebertresolve_loinc_uncased_en.md index 895d016bc9..c4a65cfde8 100644 --- a/docs/_posts/iamvarol/2021-12-31-sbluebertresolve_loinc_uncased_en.md +++ b/docs/_posts/iamvarol/2021-12-31-sbluebertresolve_loinc_uncased_en.md @@ -25,15 +25,13 @@ This model maps extracted clinical NER entities to LOINC codes using `sbluebert_ `LOINC Code` {:.btn-box} -[Live Demo](https://demo.johnsnowlabs.com/healthcare/ER_LOINC_AUGMENTED/){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/24.Improved_Entity_Resolvers_in_SparkNLP_with_sBert.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbluebertresolve_loinc_uncased_en_3.3.4_2.4_1640945648577.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbluebertresolve_loinc_uncased_en_3.3.4_2.4_1640945648577.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} ## How to use - -
{% include programmingLanguageSelectScalaPythonNLU.html %} ```python diff --git a/docs/_posts/josejuanmartinez/2022-08-12-legner_whereas_en_3_2.md b/docs/_posts/josejuanmartinez/2022-08-12-legner_whereas_en_3_2.md index 66c0fafbec..e8af48da08 100644 --- a/docs/_posts/josejuanmartinez/2022-08-12-legner_whereas_en_3_2.md +++ b/docs/_posts/josejuanmartinez/2022-08-12-legner_whereas_en_3_2.md @@ -18,7 +18,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_cuad_whereas_clause` Text Classifier to select only these paragraphs; This is a Legal NER Model, able to process WHEREAS clauses, to detect the SUBJECT (Who?), the ACTION, the OBJECT (what?) and, in some cases, the INDIRECT OBJECT (to whom?) of the clause. diff --git a/docs/_posts/josejuanmartinez/2022-08-12-legre_contract_doc_parties_en_3_2.md b/docs/_posts/josejuanmartinez/2022-08-12-legre_contract_doc_parties_en_3_2.md index 0c7654a4cf..0650b4f02e 100644 --- a/docs/_posts/josejuanmartinez/2022-08-12-legre_contract_doc_parties_en_3_2.md +++ b/docs/_posts/josejuanmartinez/2022-08-12-legre_contract_doc_parties_en_3_2.md @@ -19,7 +19,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_introduction_clause` Text Classifier to select only these paragraphs; This is a Legal Relation Extraction model, which can be used after the NER Model for extracting Parties, Document Types, Effective Dates and Aliases, called `legner_contract_doc_parties`. diff --git a/docs/_posts/josejuanmartinez/2022-08-16-legner_contract_doc_parties_en_3_2.md b/docs/_posts/josejuanmartinez/2022-08-16-legner_contract_doc_parties_en_3_2.md index edc1b985ec..fb37cf3d1f 100644 --- a/docs/_posts/josejuanmartinez/2022-08-16-legner_contract_doc_parties_en_3_2.md +++ b/docs/_posts/josejuanmartinez/2022-08-16-legner_contract_doc_parties_en_3_2.md @@ -19,7 +19,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_introduction_clause` Text Classifier to select only these paragraphs; This is a Legal NER Model, aimed to process the first page of the agreements when information can be found about: diff --git a/docs/_posts/josejuanmartinez/2022-08-22-legner_obligations_en_3_2.md b/docs/_posts/josejuanmartinez/2022-08-22-legner_obligations_en_3_2.md index 5a5416c98c..461a8b53e5 100644 --- a/docs/_posts/josejuanmartinez/2022-08-22-legner_obligations_en_3_2.md +++ b/docs/_posts/josejuanmartinez/2022-08-22-legner_obligations_en_3_2.md @@ -19,7 +19,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_cuad_obligations_clause` Text Classifier to select only these paragraphs; This Name Entity Recognition model is aimed to extract what the different parties of an agreement commit to do. We call it "obligations", but could also be called "commitments" or "agreemeents". diff --git a/docs/_posts/josejuanmartinez/2022-08-24-legpipe_obligations_en.md b/docs/_posts/josejuanmartinez/2022-08-24-legpipe_obligations_en.md index 7bccd9633f..6e237b0c4f 100644 --- a/docs/_posts/josejuanmartinez/2022-08-24-legpipe_obligations_en.md +++ b/docs/_posts/josejuanmartinez/2022-08-24-legpipe_obligations_en.md @@ -20,7 +20,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_cuad_obligations_clause` Text Classifier to select only these paragraphs; This is a Pretrained Pipeline to process agreements, more specifically the sentences where all the obligations of the parties are expressed (what they agreed upon in the contract). diff --git a/docs/_posts/josejuanmartinez/2022-08-24-legpipe_whereas_en.md b/docs/_posts/josejuanmartinez/2022-08-24-legpipe_whereas_en.md index 9b3f2a2a3b..dd44648343 100644 --- a/docs/_posts/josejuanmartinez/2022-08-24-legpipe_whereas_en.md +++ b/docs/_posts/josejuanmartinez/2022-08-24-legpipe_whereas_en.md @@ -20,7 +20,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_cuad_whereas_clause` Text Classifier to select only these paragraphs; This is a Pretrained Pipeline to show extraction of whereas clauses (Subject, Action and Object), and also the relationships between them, using two approaches: diff --git a/docs/_posts/josejuanmartinez/2022-08-24-legre_whereas_en.md b/docs/_posts/josejuanmartinez/2022-08-24-legre_whereas_en.md index c70aa70adf..ab641114a1 100644 --- a/docs/_posts/josejuanmartinez/2022-08-24-legre_whereas_en.md +++ b/docs/_posts/josejuanmartinez/2022-08-24-legre_whereas_en.md @@ -20,7 +20,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_cuad_whereas_clause` Text Classifier to select only these paragraphs; This is a Relation Extraction model to infer relations between elements in WHEREAS clauses, more specifically the SUBJECT, the ACTION and the OBJECT. There are two relations possible: `has_subject` and `has_object`. diff --git a/docs/_posts/josejuanmartinez/2022-09-06-finclf_bert_fls_en.md b/docs/_posts/josejuanmartinez/2022-09-06-finclf_bert_fls_en.md index 8c7febef69..7620afe1c9 100644 --- a/docs/_posts/josejuanmartinez/2022-09-06-finclf_bert_fls_en.md +++ b/docs/_posts/josejuanmartinez/2022-09-06-finclf_bert_fls_en.md @@ -29,7 +29,7 @@ This model was trained originally on 3,500 manually annotated sentences from Man `Specific FLS`, `Non-specific FLS`, `Not FLS` {:.btn-box} -[Live Demo](https://demo.johnsnowlabs.com/public/FINCLF_FLS/){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/finance/models/finclf_bert_fls_en_1.0.0_3.2_1662468990598.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/finance/models/finclf_bert_fls_en_1.0.0_3.2_1662468990598.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/josejuanmartinez/2022-09-27-legner_bert_indemnifications_en.md b/docs/_posts/josejuanmartinez/2022-09-27-legner_bert_indemnifications_en.md index 68194a01af..c932f8b1d8 100644 --- a/docs/_posts/josejuanmartinez/2022-09-27-legner_bert_indemnifications_en.md +++ b/docs/_posts/josejuanmartinez/2022-09-27-legner_bert_indemnifications_en.md @@ -19,7 +19,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_indemnification_clause` Text Classifier to select only these paragraphs; This is a Legal Named Entity Recognition Model to identify the Subject (who), Action (web), Object(the indemnification) and Indirect Object (to whom) from Indemnification clauses. diff --git a/docs/_posts/josejuanmartinez/2022-09-28-finre_work_experience_en.md b/docs/_posts/josejuanmartinez/2022-09-28-finre_work_experience_en.md index 69af5fdfac..5d060e8c68 100644 --- a/docs/_posts/josejuanmartinez/2022-09-28-finre_work_experience_en.md +++ b/docs/_posts/josejuanmartinez/2022-09-28-finre_work_experience_en.md @@ -20,7 +20,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole financial report. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `finclf_work_experience_item` Text Classifier to select only these paragraphs; This model allows you to analyzed present and past job positions of people, extracting relations between PERSON, ORG, ROLE and DATE. This model requires an NER with the mentioned entities, as `finner_org_per_role` and can also be combined with `finassertiondl_past_roles` to detect if the entities are mentioned to have happened in the PAST or not (although you can also infer that from the relations as `had_role_until`). @@ -32,7 +32,7 @@ This model is a `sm` model without meaningful directions in the relations (the m `has_role`, `had_role_until`, `has_role_from`, `works_for`, `has_role_in_company` {:.btn-box} -[Live Demo](https://demo.johnsnowlabs.com/finance/FINRE_WORK_EXPERIENCE){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/finance/models/finre_work_experience_en_1.0.0_3.0_1664360618647.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/finance/models/finre_work_experience_en_1.0.0_3.0_1664360618647.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/josejuanmartinez/2022-09-28-legre_indemnifications_en.md b/docs/_posts/josejuanmartinez/2022-09-28-legre_indemnifications_en.md index c4ca280c2c..2ddc41443f 100644 --- a/docs/_posts/josejuanmartinez/2022-09-28-legre_indemnifications_en.md +++ b/docs/_posts/josejuanmartinez/2022-09-28-legre_indemnifications_en.md @@ -20,7 +20,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_indemnification_clause` Text Classifier to select only these paragraphs; This is a Relation Extraction model to group the different entities extracted with the Indemnification NER model (see `legner_bert_indemnifications` in Models Hub). This model is a `sm` model without meaningful directions in the relations (the model was not trained to understand if the direction of the relation is from left to right or right to left). diff --git a/docs/_posts/josejuanmartinez/2022-11-08-finre_work_experience_md_en.md b/docs/_posts/josejuanmartinez/2022-11-08-finre_work_experience_md_en.md index c50008daac..7fd1f2744f 100644 --- a/docs/_posts/josejuanmartinez/2022-11-08-finre_work_experience_md_en.md +++ b/docs/_posts/josejuanmartinez/2022-11-08-finre_work_experience_md_en.md @@ -20,7 +20,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole financial report. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `finclf_work_experience_item` Text Classifier to select only these paragraphs; This is a `md` (medium) version of `finre_work_experience` model, trained with more data and with **unidirectional relation extractions**, meaning now the direction of the arrow matters: it goes from the source (`chunk1`) to the target (`chunk2`). @@ -32,7 +32,7 @@ This model allows you to analyzed present and past job positions of people, extr `has_role`, `had_role_until`, `has_role_from`, `works_for`, `has_role_in_company` {:.btn-box} -[Live Demo](https://demo.johnsnowlabs.com/finance/FINRE_WORK_EXPERIENCE){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos){:.button.button-orange} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/finance/models/finre_work_experience_md_en_1.0.0_3.0_1667922980930.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/finance/models/finre_work_experience_md_en_1.0.0_3.0_1667922980930.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/_posts/josejuanmartinez/2022-11-09-legner_termination_en.md b/docs/_posts/josejuanmartinez/2022-11-09-legner_termination_en.md index 2fb6d11c72..b5396ce68a 100644 --- a/docs/_posts/josejuanmartinez/2022-11-09-legner_termination_en.md +++ b/docs/_posts/josejuanmartinez/2022-11-09-legner_termination_en.md @@ -20,7 +20,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_termination_clause` Text Classifier to select only these paragraphs; This is a NER model which extracts information from Termination Clauses, like the subject (Who? Which party?) the action (verb) the object (What?) and the Indirect Object (to Whom?). diff --git a/docs/_posts/josejuanmartinez/2022-12-01-legner_contract_doc_parties_md_en.md b/docs/_posts/josejuanmartinez/2022-12-01-legner_contract_doc_parties_md_en.md index 668862e189..7e79860fc1 100644 --- a/docs/_posts/josejuanmartinez/2022-12-01-legner_contract_doc_parties_md_en.md +++ b/docs/_posts/josejuanmartinez/2022-12-01-legner_contract_doc_parties_md_en.md @@ -20,7 +20,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_introduction_clause` Text Classifier to select only these paragraphs; This is a Legal NER Model, aimed to process the first page of the agreements when information can be found about: diff --git a/docs/_posts/josejuanmartinez/2022-12-01-legner_indemnifications_md_en.md b/docs/_posts/josejuanmartinez/2022-12-01-legner_indemnifications_md_en.md index c9e5f692f3..631e397030 100644 --- a/docs/_posts/josejuanmartinez/2022-12-01-legner_indemnifications_md_en.md +++ b/docs/_posts/josejuanmartinez/2022-12-01-legner_indemnifications_md_en.md @@ -20,7 +20,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_indemnification_clause` Text Classifier to select only these paragraphs; This is a Legal Named Entity Recognition Model to identify the Subject (who), Action (web), Object(the indemnification) and Indirect Object (to whom) from Indemnification clauses. diff --git a/docs/_posts/josejuanmartinez/2022-12-01-legner_termination_md_en.md b/docs/_posts/josejuanmartinez/2022-12-01-legner_termination_md_en.md index 0e77aad34e..497c703f4e 100644 --- a/docs/_posts/josejuanmartinez/2022-12-01-legner_termination_md_en.md +++ b/docs/_posts/josejuanmartinez/2022-12-01-legner_termination_md_en.md @@ -20,7 +20,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_termination_clause` Text Classifier to select only these paragraphs; This is a NER model which extracts information from Termination Clauses, like the subject (Who? Which party?) the action (verb) the object (What?) and the Indirect Object (to Whom?). diff --git a/docs/_posts/josejuanmartinez/2022-12-01-legner_warranty_md_en.md b/docs/_posts/josejuanmartinez/2022-12-01-legner_warranty_md_en.md index 4ed8a857ca..29f2ebae84 100644 --- a/docs/_posts/josejuanmartinez/2022-12-01-legner_warranty_md_en.md +++ b/docs/_posts/josejuanmartinez/2022-12-01-legner_warranty_md_en.md @@ -20,7 +20,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_warranty_clause` Text Classifier to select only these paragraphs; This is a Legal Named Entity Recognition Model to identify the Subject (who), Action (what), Object(the indemnification) and Indirect Object (to whom) from Warranty clauses. diff --git a/docs/_posts/josejuanmartinez/2022-12-01-legner_whereas_md_en.md b/docs/_posts/josejuanmartinez/2022-12-01-legner_whereas_md_en.md index 34f175f3b3..d4f5107999 100644 --- a/docs/_posts/josejuanmartinez/2022-12-01-legner_whereas_md_en.md +++ b/docs/_posts/josejuanmartinez/2022-12-01-legner_whereas_md_en.md @@ -20,7 +20,7 @@ use_language_switcher: "Python-Scala-Java" ## Description IMPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_cuad_whereas_clause` Text Classifier to select only these paragraphs; This is a Legal NER Model, able to process WHEREAS clauses, to detect the SUBJECT (Who?), the ACTION, the OBJECT (what?) and, in some cases, the INDIRECT OBJECT (to whom?) of the clause. diff --git a/docs/_posts/josejuanmartinez/2023-01-21-legner_contract_doc_parties_lg_en.md b/docs/_posts/josejuanmartinez/2023-01-21-legner_contract_doc_parties_lg_en.md index e29d8f4f4e..85ea9ed40e 100644 --- a/docs/_posts/josejuanmartinez/2023-01-21-legner_contract_doc_parties_lg_en.md +++ b/docs/_posts/josejuanmartinez/2023-01-21-legner_contract_doc_parties_lg_en.md @@ -21,7 +21,7 @@ use_language_switcher: "Python-Scala-Java" ## Description MPORTANT: Don't run this model on the whole legal agreement. Instead: -- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings_JSL) in Finance or Legal as inspiration; +- Split by paragraphs. You can use [notebook 1](https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/tutorials/Certification_Trainings) in Finance or Legal as inspiration; - Use the `legclf_introduction_clause` Text Classifier to select only these paragraphs; This is a Legal NER Model, aimed to process the first page of the agreements when information can be found about: diff --git a/docs/_posts/muhammetsnts/2021-10-05-sbiobertresolve_rxnorm_ndc_en.md b/docs/_posts/muhammetsnts/2021-10-05-sbiobertresolve_rxnorm_ndc_en.md index 1d5ace6fec..3bed0259c0 100644 --- a/docs/_posts/muhammetsnts/2021-10-05-sbiobertresolve_rxnorm_ndc_en.md +++ b/docs/_posts/muhammetsnts/2021-10-05-sbiobertresolve_rxnorm_ndc_en.md @@ -26,7 +26,7 @@ This model maps `DRUG ` entities to RxNorm codes and their [National Drug Codes `RxNorm Codes`, `NDC Codes` {:.btn-box} -[Live Demo](https://demo.johnsnowlabs.com/healthcare/ER_RXNORM_NDC/){:.button.button-orange} +[Live Demo](https://nlp.johnsnowlabs.com/demos/){:.button.button-orange} [Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/3.Clinical_Entity_Resolvers.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} [Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_rxnorm_ndc_en_3.2.3_2.4_1633424811842.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden} [Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/sbiobertresolve_rxnorm_ndc_en_3.2.3_2.4_1633424811842.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} diff --git a/docs/demos/databricks_solution_accelerators.md b/docs/demos/databricks_solution_accelerators.md index ed688ec43a..115f3629d4 100644 --- a/docs/demos/databricks_solution_accelerators.md +++ b/docs/demos/databricks_solution_accelerators.md @@ -41,7 +41,7 @@ data: actions: - text: Databricks Notebook type: normal - url: https://databricks.com/solutions/accelerators/nlp-oncology/ + url: https://databricks.com/solutions/accelerators/nlp-oncology - title: Adverse Drug Event Detection id: adverse_drug_event_detection image: @@ -50,7 +50,7 @@ data: actions: - text: Databricks Notebook type: normal - url: https://databricks.com/solutions/accelerators/adverse-drug-event-detection/ + url: https://databricks.com/solutions/accelerators/adverse-drug-event-detection - title: Medicare Risk Adjustment id: medicare_risk_adjustment image: @@ -59,15 +59,14 @@ data: actions: - text: Databricks Notebook type: normal - url: https://www.databricks.com/solutions/accelerators/medicare-risk-adjustment/ - - title: Toxicity Detection for Gaming - hide: yes - id: toxicity_detection_gaming + url: https://www.databricks.com/solutions/accelerators/medicare-risk-adjustment + - title: Knowledge Graph + id: knowledge_graph image: - src: /assets/images/Extract_public_companies_key_data_10_filings.svg - excerpt: Foster healthier gaming communities with real-time detection of toxic language. + src: /assets/images/Detect_demographics_and_vital_signs_using_rules.svg + excerpt: Build patient cohorts by identifying commonalities between entities. actions: - text: Databricks Notebook type: normal - url: https://databricks.com/solutions/accelerators/toxicity-detection-for-gaming + url: https://www.databricks.com/solutions/accelerators/cohort-building --- \ No newline at end of file diff --git a/docs/en/alab/annotation_labs_releases/release_notes_2_8_0.md b/docs/en/alab/annotation_labs_releases/release_notes_2_8_0.md index ea8085f936..9d056c7dd9 100644 --- a/docs/en/alab/annotation_labs_releases/release_notes_2_8_0.md +++ b/docs/en/alab/annotation_labs_releases/release_notes_2_8_0.md @@ -32,7 +32,7 @@ New features offered by Annotation Lab: - [Download model dependencies](/docs/en/alab/models_hub#download-of-model-dependencies) is now automatic. - The project configuration box can now be edited in full screen mode. - [Trim leading and ending spaces in annotated chunks](/docs/en/alab/annotation#trim-leading-and-ending-spaces-in-annotated-chunks). -- [Reserved words](/docs/en/alab/project_setup#reserved-words-cannot-be-used-in-project-names) cannot be used in project names. +- [Reserved words](/docs/en/alab/project_creation#reserved-words-cannot-be-used-in-project-names) cannot be used in project names. - Task numbering now start from 1. - 'a' was removed as hotkey for VisualNER multi-chunk selection. Going forward only use 'shift' key for chunk selection. - Only alphanumeric characters can be used as the Task Tag Names. diff --git a/docs/en/alab/annotation_labs_releases/release_notes_3_0_0.md b/docs/en/alab/annotation_labs_releases/release_notes_3_0_0.md index ad97143e61..dde551362a 100644 --- a/docs/en/alab/annotation_labs_releases/release_notes_3_0_0.md +++ b/docs/en/alab/annotation_labs_releases/release_notes_3_0_0.md @@ -22,13 +22,13 @@ We are very excited to release Annotation Lab 3.0.0 with support for Floating Li ### Highlights - Annotation Lab now supports [floating licenses](/docs/en/alab/byol#support-for-floating-licenses) with different scopes (ocr: training, ocr: inference, healthcare: inference, healthcare: training). Depending on the scope of the available license, users can perform model training and/or deploy preannotation servers. Licenses are a must only for training Spark NLP for Healthcare models and for deploying Spark NLP for Healthcare models as preannotation servers. -- [Parallel Trainings](/docs/en/alab/active_learning#deploy-a-new-training-job) and [Preannotations](/docs/en/alab/preannotations#start-preannotation). Annotation Lab now offers support for running model training and document preannotation across multiple projects and/or teams in parallel. If the infrastructure dedicated to the Annotation Lab includes sufficient resources, each team/project can run smoothly without being blocked. +- [Parallel Trainings](/docs/en/alab/active_learning#deploy-a-new-training-job) and [Preannotations](/docs/en/alab/preannotation#start-preannotation). Annotation Lab now offers support for running model training and document preannotation across multiple projects and/or teams in parallel. If the infrastructure dedicated to the Annotation Lab includes sufficient resources, each team/project can run smoothly without being blocked. - On demand deployment of preannotation servers and training jobs: - [Deploy a new training job](/docs/en/alab/active_learning#deploy-a-new-training-job) - - [Deploy a new preannotation server](/docs/en/alab/preannotations#start-preannotation) - - [OCR and Visual NER servers](/docs/en/alab/visual_ner#ocr-and-visual-ner-servers) + - [Deploy a new preannotation server](/docs/en/alab/preannotation#start-preannotation) + - The infrastucture page now hosts a new tab for managing [preannotation, training and OCR servers.](/docs/en/alab/infrastructure#management-of-preannotation-and-training-servers) -- New options available on [preannotate](/docs/en/alab/preannotations#start-preannotation) action. +- New options available on [preannotate](/docs/en/alab/preannotation#start-preannotation) action. - Updates for the [license page](/docs/en/alab/byol#license-page).
diff --git a/docs/en/alab/project_creation.md b/docs/en/alab/project_creation.md index d6471c71e8..886c7033f1 100644 --- a/docs/en/alab/project_creation.md +++ b/docs/en/alab/project_creation.md @@ -12,6 +12,7 @@ show_nav: true sidebar: nav: annotation-lab --- +
## New project @@ -22,6 +23,8 @@ Every project in Annotation Lab should have the following information: You can create a new project using the dedicated wizard which will guide users through each step of the project creation and configuration process. Those steps are illustrated below. +
+ ### Project Description To open the project creation wizard click on the `+ New Project` button on the `Projects Dashboard`, then provide the following information: @@ -39,6 +42,7 @@ To open the project creation wizard click on the `+ New Project` button on the ` +
### Adding Team Members @@ -60,6 +64,7 @@ In the `Add Team Member` page users can add/remove/update the team members even > **NOTE:** The priority assigned for users in the `Add Team Member` page is taken into account by the Model Training script for differentiating among the available ground truth completions (when more than one is available for a task) in view of choosing the higer priority completion which will be used for model training. Learn more [here](/docs/en/alab/training_configurations#selection-of-completions). +
### Project Configuration @@ -67,21 +72,29 @@ The Project Configuration itself is a multi-step process. The wizard will guide ![projectConfiguration](https://user-images.githubusercontent.com/46840490/193033349-534cc2ab-2e5a-4caa-a050-0ee650949b21.gif) +
+ ## Clone You can create a copy of a project, by using the Clone option. The option to clone the project is also listed in the kebab menu of each project. The cloned project is differentiated as it contains cloned suffix in its project name. +
+ ## Export Projects can be exported. The option to export a project is listed in the kebab menu of each project. All project-related items such as tasks, project configuration, project members, task assignments, and comments are included in the export file. > **NOTE:** Project export does not contain the model trained in the project as models are independent and not attached to a particular project. - + +
+ ## Import A project can be imported by uploading the project zip archive in the upload dialog box. When the project is imported back to Annotation Lab, all elements of the original project configuration will be included in the new copy. - + +
+ ## Project Grouping As the number of projects can grow significantly over time, for an easier management and organization of those, Annotation Lab allows project grouping. As such, a project owner can assign a group to one or several of his/her projects. Each group can be assigned a color which will be used to highlight projects included in that group. Once a project is assigned to a group, the group name will appear as a tag on the project tile. At any time a project can be remove from one group and added to another group. @@ -94,5 +107,4 @@ Projects can be organized in custom groups, and each project card will inherit t ![DashboardGroupGIF](https://user-images.githubusercontent.com/46840490/193201637-57a7e7b6-9d25-48b4-9196-e6bed61fa2ad.gif) - - +
\ No newline at end of file diff --git a/docs/en/display.md b/docs/en/display.md index b5da963d0c..87bc4fdda7 100644 --- a/docs/en/display.md +++ b/docs/en/display.md @@ -148,7 +148,7 @@ The following image gives an example of html output that is obtained for a coupl ### Visualize entity resolution -**Entity resolution** refers to the normalization of named entities predicted by Spark NLP with respect to standard terminologies such as ICD-10, SNOMED, RxNorm etc. You can read more about the available entity resolvers here. +**Entity resolution** refers to the normalization of named entities predicted by Spark NLP with respect to standard terminologies such as ICD-10, SNOMED, RxNorm etc. You can read more about the available entity resolvers here. The **EntityResolverVisualizer** will automatically display on top of the NER label the standard code (ICD10 CM, PCS, ICDO; CPT) that corresponds to that entity as well as the short description of the code. If no resolution code could be identified a regular NER-type of visualization will be displayed. diff --git a/docs/en/jsl/jsl_release_notes.md b/docs/en/jsl/jsl_release_notes.md index 7487b74cb2..3c5c3ff29c 100644 --- a/docs/en/jsl/jsl_release_notes.md +++ b/docs/en/jsl/jsl_release_notes.md @@ -25,10 +25,10 @@ The John Snow Labs 4.4.6 Library released with the following pre-installed and r | Library | Version | |-----------------------------------------------------------------------------|---------| -| [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/ocr_release_notes) | `4.4.1` | +| [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/spark_ocr_versions/ocr_release_notes) | `4.4.1` | | [Enterprise NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/licensed_annotators) | `4.4.2` | -| [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/financial_release_notes) | `1.X.X` | -| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/legal_release_notes) | `1.X.X` | +| [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/financial_release_notes) | `1.X.X` | +| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/legal_release_notes) | `1.X.X` | | [NLU](https://github.com/JohnSnowLabs/nlu/releases) | `4.2.0` | | [Spark-NLP-Display](https://nlp.johnsnowlabs.com/docs/en/jsl/display) | `4.1` | | [Spark-NLP](https://github.com/JohnSnowLabs/spark-nlp/releases/) | `4.4.1` | @@ -58,10 +58,10 @@ The John Snow Labs 4.4.5 Library released with the following pre-installed and r | Library | Version | |-----------------------------------------------------------------------------|---------| -| [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/ocr_release_notes) | `4.4.0` | +| [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/spark_ocr_versions/ocr_release_notes) | `4.4.0` | | [Enterprise NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/licensed_annotators) | `4.4.1` | -| [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/financial_release_notes) | `1.X.X` | -| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/legal_release_notes) | `1.X.X` | +| [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/financial_release_notes) | `1.X.X` | +| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/legal_release_notes) | `1.X.X` | | [NLU](https://github.com/JohnSnowLabs/nlu/releases) | `4.2.0` | | [Spark-NLP-Display](https://nlp.johnsnowlabs.com/docs/en/jsl/display) | `4.1` | | [Spark-NLP](https://github.com/JohnSnowLabs/spark-nlp/releases/) | `4.4.1` | @@ -77,10 +77,10 @@ The John Snow Labs 4.4.4 Library released with the following pre-installed and r | Library | Version | |-----------------------------------------------------------------------------|---------| -| [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/ocr_release_notes) | `4.4.0` | +| [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/spark_ocr_versions/ocr_release_notes) | `4.4.0` | | [Enterprise NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/licensed_annotators) | `4.4.0` | -| [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/financial_release_notes) | `1.X.X` | -| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/legal_release_notes) | `1.X.X` | +| [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/financial_release_notes) | `1.X.X` | +| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/legal_release_notes) | `1.X.X` | | [NLU](https://github.com/JohnSnowLabs/nlu/releases) | `4.2.0` | | [Spark-NLP-Display](https://nlp.johnsnowlabs.com/docs/en/jsl/display) | `4.1` | | [Spark-NLP](https://github.com/JohnSnowLabs/spark-nlp/releases/) | `4.4.1` | @@ -96,10 +96,10 @@ The John Snow Labs 4.4.4 Library released with the following pre-installed and r | Library | Version | |-----------------------------------------------------------------------------|---------| -| [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/ocr_release_notes) | `4.4.0` | +| [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/spark_ocr_versions/ocr_release_notes) | `4.4.0` | | [Enterprise NLP](https://sparknlp.org/docs/en/annotators) | `4.4.0` | -| [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/financial_release_notes) | `1.X.X` | -| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/legal_release_notes) | `1.X.X` | +| [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/financial_release_notes) | `1.X.X` | +| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/legal_release_notes) | `1.X.X` | | [NLU](https://github.com/JohnSnowLabs/nlu/releases) | `4.2.0` | | [Spark-NLP-Display](https://nlp.johnsnowlabs.com/docs/en/jsl/display) | `4.1` | | [Spark-NLP](https://github.com/JohnSnowLabs/spark-nlp/releases/) | `4.4.1` | @@ -118,7 +118,7 @@ The John Snow Labs 4.4.4 Library released with the following pre-installed and r | [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/spark_ocr_versions/ocr_release_notes) | `4.4.0` | | [Enterprise NLP](https://nlp.johnsnowlabs.com/docs/en/licensed_annotators) | `4.4.0` | | [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/financial_release_notes) | `1.X.X` | -| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/legal_release_notes) | `1.X.X` | +| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/legal_release_notes) | `1.X.X` | | [NLU](https://github.com/JohnSnowLabs/nlu/releases) | `4.2.0` | | [Spark-NLP-Display](https://nlp.johnsnowlabs.com/docs/en/display) | `4.1` | | [Spark-NLP](https://github.com/JohnSnowLabs/spark-nlp/releases/) | `4.4.1` | @@ -137,7 +137,7 @@ The John Snow Labs 4.4.3 Library released with the following pre-installed and r | [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/spark_ocr_versions/ocr_release_notes) | `4.4.0` | | [Enterprise NLP](https://nlp.johnsnowlabs.com/docs/en/licensed_annotators) | `4.4.0` | | [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/financial_release_notes) | `1.X.X` | -| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/legal_release_notes) | `1.X.X` | +| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/legal_release_notes) | `1.X.X` | | [NLU](https://github.com/JohnSnowLabs/nlu/releases) | `4.2.0` | | [Spark-NLP-Display](https://nlp.johnsnowlabs.com/docs/en/display) | `4.1` | | [Spark-NLP](https://github.com/JohnSnowLabs/spark-nlp/releases/) | `4.4.1` | @@ -153,7 +153,7 @@ The John Snow Labs 4.4.2 Library released with the following pre-installed and r | [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/spark_ocr_versions/ocr_release_notes) | `4.4.0` | | [Enterprise NLP](https://nlp.johnsnowlabs.com/docs/en/licensed_annotators) | `4.4.0` | | [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/financial_release_notes) | `1.X.X` | -| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/legal_release_notes) | `1.X.X` | +| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/legal_release_notes) | `1.X.X` | | [NLU](https://github.com/JohnSnowLabs/nlu/releases) | `4.2.0` | | [Spark-NLP-Display](https://nlp.johnsnowlabs.com/docs/en/display) | `4.1` | | [Spark-NLP](https://github.com/JohnSnowLabs/spark-nlp/releases/) | `4.4.0` | @@ -169,7 +169,7 @@ The John Snow Labs 4.4.1 Library released with the following pre-installed and r | [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/spark_ocr_versions/ocr_release_notes) | `4.3.3` | | [Enterprise NLP](https://nlp.johnsnowlabs.com/docs/en/licensed_annotators) | `4.4.0` | | [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/financial_release_notes) | `1.X.X` | -| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/legal_release_notes) | `1.X.X` | +| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/legal_release_notes) | `1.X.X` | | [NLU](https://github.com/JohnSnowLabs/nlu/releases) | `4.2.0` | | [Spark-NLP-Display](https://nlp.johnsnowlabs.com/docs/en/display) | `4.1` | | [Spark-NLP](https://github.com/JohnSnowLabs/spark-nlp/releases/) | `4.4.0` | @@ -185,7 +185,7 @@ The John Snow Labs 4.4.0 Library released with the following pre-installed and r | [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/spark_ocr_versions/ocr_release_notes) | `4.3.3` | | [Enterprise NLP](https://nlp.johnsnowlabs.com/docs/en/licensed_annotators) | `4.4.0` | | [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/financial_release_notes) | `1.X.X` | -| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/legal_release_notes) | `1.X.X` | +| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/legal_release_notes) | `1.X.X` | | [NLU](https://github.com/JohnSnowLabs/nlu/releases) | `4.2.0` | | [Spark-NLP-Display](https://nlp.johnsnowlabs.com/docs/en/display) | `4.1` | | [Spark-NLP](https://github.com/JohnSnowLabs/spark-nlp/releases/) | `4.4.0` | @@ -201,7 +201,7 @@ The John Snow Labs 4.3.5 Library released with the following pre-installed and r | [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/spark_ocr_versions/ocr_release_notes) | `4.3.3` | | [Enterprise NLP](https://nlp.johnsnowlabs.com/docs/en/licensed_annotators) | `4.3.2` | | [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/financial_release_notes) | `1.X.X` | -| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/legal_release_notes) | `1.X.X` | +| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/legal_release_notes) | `1.X.X` | | [NLU](https://github.com/JohnSnowLabs/nlu/releases) | `4.2.0` | | [Spark-NLP-Display](https://nlp.johnsnowlabs.com/docs/en/display) | `4.1` | | [Spark-NLP](https://github.com/JohnSnowLabs/spark-nlp/releases/) | `4.3.2` | @@ -217,7 +217,7 @@ The John Snow Labs 4.3.4 Library released with the following pre-installed and r | [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/spark_ocr_versions/ocr_release_notes) | `4.3.3` | | [Enterprise NLP](https://nlp.johnsnowlabs.com/docs/en/licensed_annotators) | `4.3.1` | | [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/financial_release_notes) | `1.X.X` | -| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/legal_release_notes) | `1.X.X` | +| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/legal_release_notes) | `1.X.X` | | [NLU](https://github.com/JohnSnowLabs/nlu/releases) | `4.2.0` | | [Spark-NLP-Display](https://nlp.johnsnowlabs.com/docs/en/display) | `4.1` | | [Spark-NLP](https://github.com/JohnSnowLabs/spark-nlp/releases/) | `4.3.2` | @@ -233,7 +233,7 @@ The John Snow Labs 4.3.3 Library released with the following pre-installed and r | [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/spark_ocr_versions/ocr_release_notes) | `4.3.1` | | [Enterprise NLP](https://nlp.johnsnowlabs.com/docs/en/licensed_annotators) | `4.3.0` | | [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/financial_release_notes) | `1.X.X` | -| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/legal_release_notes) | `1.X.X` | +| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/legal_release_notes) | `1.X.X` | | [NLU](https://github.com/JohnSnowLabs/nlu/releases) | `4.0.1rc6` | | [Spark-NLP-Display](https://nlp.johnsnowlabs.com/docs/en/display) | `4.1` | | [Spark-NLP](https://github.com/JohnSnowLabs/spark-nlp/releases/) | `4.3.0` | @@ -249,7 +249,7 @@ The John Snow Labs 4.3.2 Library released with the following pre-installed and r | [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/spark_ocr_versions/ocr_release_notes) | `4.3.0` | | [Enterprise NLP](https://nlp.johnsnowlabs.com/docs/en/licensed_annotators) | `4.3.0` | | [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/financial_release_notes) | `1.X.X` | -| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/legal_release_notes) | `1.X.X` | +| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/legal_release_notes) | `1.X.X` | | [NLU](https://github.com/JohnSnowLabs/nlu/releases) | `4.0.1rc6` | | [Spark-NLP-Display](https://nlp.johnsnowlabs.com/docs/en/display) | `4.1` | | [Spark-NLP](https://github.com/JohnSnowLabs/spark-nlp/releases/) | `4.3.0` | @@ -265,7 +265,7 @@ The John Snow Labs 4.3.1 Library released with the following pre-installed and r | [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/spark_ocr_versions/ocr_release_notes) | `4.3.0` | | [Enterprise NLP](https://nlp.johnsnowlabs.com/docs/en/licensed_annotators) | `4.3.0` | | [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/financial_release_notes) | `1.X.X` | -| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/legal_release_notes) | `1.X.X` | +| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/legal_release_notes) | `1.X.X` | | [NLU](https://github.com/JohnSnowLabs/nlu/releases) | `4.0.1rc5` | | [Spark-NLP-Display](https://nlp.johnsnowlabs.com/docs/en/display) | `4.1` | | [Spark-NLP](https://github.com/JohnSnowLabs/spark-nlp/releases/) | `4.3.0` | @@ -281,7 +281,7 @@ The John Snow Labs 4.3.0 Library released with the following pre-installed and r | [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/spark_ocr_versions/ocr_release_notes) | `4.3.0` | | [Enterprise NLP](https://nlp.johnsnowlabs.com/docs/en/licensed_annotators) | `4.3.0` | | [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/financial_release_notes) | `1.X.X` | -| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/legal_release_notes) | `1.X.X` | +| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/legal_release_notes) | `1.X.X` | | [NLU](https://github.com/JohnSnowLabs/nlu/releases) | `4.0.1rc4` | | [Spark-NLP-Display](https://nlp.johnsnowlabs.com/docs/en/display) | `4.1` | | [Spark-NLP](https://github.com/JohnSnowLabs/spark-nlp/releases/) | `4.3.0` | @@ -297,7 +297,7 @@ The John Snow Labs 4.2.9 Library released with the following pre-installed and r | [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/spark_ocr_versions/ocr_release_notes) | `4.3.0` | | [Enterprise NLP](https://nlp.johnsnowlabs.com/docs/en/licensed_annotators) | `4.2.8` | | [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/financial_release_notes) | `1.X.X` | -| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/legal_release_notes) | `1.X.X` | +| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/legal_release_notes) | `1.X.X` | | [NLU](https://github.com/JohnSnowLabs/nlu/releases) | `4.0.1rc4` | | [Spark-NLP-Display](https://nlp.johnsnowlabs.com/docs/en/display) | `4.1` | | [Spark-NLP](https://github.com/JohnSnowLabs/spark-nlp/releases/) | `4.2.8` | @@ -313,7 +313,7 @@ The John Snow Labs 4.2.8 Library released with the following pre-installed and r | [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/spark_ocr_versions/ocr_release_notes) | `4.3.0` | | [Enterprise NLP](https://nlp.johnsnowlabs.com/docs/en/licensed_annotators) | `4.2.8` | | [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/financial_release_notes) | `1.X.X` | -| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/legal_release_notes) | `1.X.X` | +| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/legal_release_notes) | `1.X.X` | | [NLU](https://github.com/JohnSnowLabs/nlu/releases) | `4.0.1rc4` | | [Spark-NLP-Display](https://nlp.johnsnowlabs.com/docs/en/display) | `4.1` | | [Spark-NLP](https://github.com/JohnSnowLabs/spark-nlp/releases/) | `4.2.8` | @@ -329,7 +329,7 @@ The John Snow Labs 4.2.5 Library released with the following pre-installed and r | [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/spark_ocr_versions/ocr_release_notes) | `4.2.4` | | [Enterprise NLP](https://nlp.johnsnowlabs.com/docs/en/licensed_annotators) | `4.2.4` | | [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/financial_release_notes) | `1.X.X` | -| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/legal_release_notes) | `1.X.X` | +| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/legal_release_notes) | `1.X.X` | | [NLU](https://github.com/JohnSnowLabs/nlu/releases) | `4.0.1rc4` | | [Spark-NLP-Display](https://nlp.johnsnowlabs.com/docs/en/display) | `4.1` | | [Spark-NLP](https://github.com/JohnSnowLabs/spark-nlp/releases/) | `4.2.4` | @@ -346,7 +346,7 @@ The John Snow Labs 4.2.4 Library released with the following pre-installed and r | [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/spark_ocr_versions/ocr_release_notes) | `4.2.1` | | [Enterprise NLP](https://nlp.johnsnowlabs.com/docs/en/licensed_annotators) | `4.2.4` | | [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/financial_release_notes) | `1.X.X` | -| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/legal_release_notes) | `1.X.X` | +| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/legal_release_notes) | `1.X.X` | | [NLU](https://github.com/JohnSnowLabs/nlu/releases) | `4.0.1rc4` | | [Spark-NLP-Display](https://nlp.johnsnowlabs.com/docs/en/display) | `4.1` | | [Spark-NLP](https://github.com/JohnSnowLabs/spark-nlp/releases/) | `4.2.4` | @@ -363,7 +363,7 @@ The John Snow Labs 4.2.3 Library released with the following pre-installed and r | [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/spark_ocr_versions/ocr_release_notes) | `4.2.1` | | [Enterprise NLP](https://nlp.johnsnowlabs.com/docs/en/licensed_annotators) | `4.2.3` | | [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/financial_release_notes) | `1.X.X` | -| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/legal_release_notes) | `1.X.X` | +| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/legal_release_notes) | `1.X.X` | | [NLU](https://github.com/JohnSnowLabs/nlu/releases) | `4.0.1rc4` | | [Spark-NLP-Display](https://nlp.johnsnowlabs.com/docs/en/display) | `4.1` | | [Spark-NLP](https://github.com/JohnSnowLabs/spark-nlp/releases/) | `4.2.4` | @@ -380,7 +380,7 @@ The John Snow Labs 4.2.2 Library released with the following pre-installed and r | [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/spark_ocr_versions/ocr_release_notes) | `4.2.0` | | [Enterprise NLP](https://nlp.johnsnowlabs.com/docs/en/licensed_annotators) | `4.2.2` | | [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/financial_release_notes) | `1.X.X` | -| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/legal_release_notes) | `1.X.X` | +| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/legal_release_notes) | `1.X.X` | | [NLU](https://github.com/JohnSnowLabs/nlu/releases) | `4.0.1rc4` | | [Spark-NLP-Display](https://nlp.johnsnowlabs.com/docs/en/display) | `4.1` | | [Spark-NLP](https://github.com/JohnSnowLabs/spark-nlp/releases/) | `4.2.2` | @@ -397,7 +397,7 @@ The John Snow Labs 4.2.1 Library released with the following pre-installed and r | [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/spark_ocr_versions/ocr_release_notes) | `4.1.0` | | [Enterprise NLP](https://nlp.johnsnowlabs.com/docs/en/licensed_annotators) | `4.2.0` | | [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/financial_release_notes) | `1.X.X` | -| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/legal_release_notes) | `1.X.X` | +| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/legal_release_notes) | `1.X.X` | | [NLU](https://github.com/JohnSnowLabs/nlu/releases) | `4.0.1rc4` | | [Spark-NLP-Display](https://nlp.johnsnowlabs.com/docs/en/display) | `4.1` | | [Spark-NLP](https://github.com/JohnSnowLabs/spark-nlp/releases/) | `4.2.1` | @@ -415,7 +415,7 @@ The John Snow Labs 4.2.0 Library released with the following pre-installed and r | [Visual NLP](https://nlp.johnsnowlabs.com/docs/en/spark_ocr_versions/ocr_release_notes) | `4.0.0` | | [Enterprise NLP](https://nlp.johnsnowlabs.com/docs/en/licensed_annotators) | `4.2.0` | | [Finance NLP](https://nlp.johnsnowlabs.com/docs/en/financial_release_notes) | `1.X.X` | -| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/jsl/legal_release_notes) | `1.X.X` | +| [Legal NLP](https://nlp.johnsnowlabs.com/docs/en/legal_release_notes) | `1.X.X` | | [NLU](https://github.com/JohnSnowLabs/nlu/releases) | `4.0.1rc4` | | [Spark-NLP-Display](https://nlp.johnsnowlabs.com/docs/en/display) | `4.1` | | [Spark-NLP](https://github.com/JohnSnowLabs/spark-nlp/releases/) | `4.2.0` | diff --git a/docs/en/jsl/release_notes.md b/docs/en/jsl/release_notes.md index 1865a6541d..014452e0cb 100644 --- a/docs/en/jsl/release_notes.md +++ b/docs/en/jsl/release_notes.md @@ -2774,7 +2774,7 @@ and their respective ISO-639-3 and ISO 630-2 codes are : #### Additional NLU resources * [140+ NLU Tutorials](https://nlp.johnsnowlabs.com/docs/en/jsl/notebooks) -* [NLU in Action](https://nlp.johnsnowlabs.com/demo) +* [NLU in Action](https://nlp.johnsnowlabs.com/demos) * [Streamlit visualizations docs](https://nlp.johnsnowlabs.com/docs/en/jsl/streamlit_viz_examples) * The complete list of all 4000+ models & pipelines in 200+ languages is available on [Models Hub](https://nlp.johnsnowlabs.com/models). * [Spark NLP publications](https://medium.com/spark-nlp) @@ -2837,7 +2837,7 @@ Integrates models from [Spark NLP For Healthcare 3.4.2](https://nlp.johnsnowlabs #### Additional NLU resources * [140+ NLU Tutorials](https://nlp.johnsnowlabs.com/docs/en/jsl/notebooks) -* [NLU in Action](https://nlp.johnsnowlabs.com/demo) +* [NLU in Action](https://nlp.johnsnowlabs.com/demos) * [Streamlit visualizations docs](https://nlp.johnsnowlabs.com/docs/en/jsl/streamlit_viz_examples) * The complete list of all 4000+ models & pipelines in 200+ languages is available on [Models Hub](https://nlp.johnsnowlabs.com/models). * [Spark NLP publications](https://medium.com/spark-nlp) @@ -2966,7 +2966,7 @@ and Relation extractors for Temporality and Causality of Drugs and Adverse Event #### Additional NLU resources * [140+ NLU Tutorials](https://nlp.johnsnowlabs.com/docs/en/jsl/notebooks) -* [NLU in Action](https://nlp.johnsnowlabs.com/demo) +* [NLU in Action](https://nlp.johnsnowlabs.com/demos) * [Streamlit visualizations docs](https://nlp.johnsnowlabs.com/docs/en/jsl/streamlit_viz_examples) * The complete list of all 4000+ models & pipelines in 200+ languages is available on [Models Hub](https://nlp.johnsnowlabs.com/models). * [Spark NLP publications](https://medium.com/spark-nlp) @@ -3180,7 +3180,7 @@ Integration for the 28 new models from the amazing [Spark NLP for healthcare 3.4 * [NLU OCR tutorial notebook](https://colab.research.google.com/github/JohnSnowLabs/nlu/blob/master/examples/colab/ocr/ocr_for_img_pdf_docx_files.ipynb) * [140+ NLU Tutorials](https://nlp.johnsnowlabs.com/docs/en/jsl/notebooks) -* [NLU in Action](https://nlp.johnsnowlabs.com/demo) +* [NLU in Action](https://nlp.johnsnowlabs.com/demos) * [Streamlit visualizations docs](https://nlp.johnsnowlabs.com/docs/en/jsl/streamlit_viz_examples) * The complete list of all 4000+ models & pipelines in 200+ languages is available on [Models Hub](https://nlp.johnsnowlabs.com/models). * [Spark NLP publications](https://medium.com/spark-nlp) @@ -3481,7 +3481,7 @@ Added documentation section regarding compatibility of NLU, Spark NLP and Spark * [Streamlit visualizations docs](https://nlp.johnsnowlabs.com/docs/en/jsl/streamlit_viz_examples) * The complete list of all 4000+ models & pipelines in 200+ languages is available on [Models Hub](https://nlp.johnsnowlabs.com/models). * [Spark NLP publications](https://medium.com/spark-nlp) -* [NLU in Action](https://nlp.johnsnowlabs.com/demo) +* [NLU in Action](https://nlp.johnsnowlabs.com/demos) * [NLU documentation](https://nlp.johnsnowlabs.com/docs/en/jsl/install) * [Discussions](https://github.com/JohnSnowLabs/spark-nlp/discussions) Engage with other community members, share ideas, and show off how you use Spark NLP and NLU! @@ -3794,7 +3794,7 @@ you have a Pyarrow version installed that works with your Pyspark version. * [Streamlit visualizations docs](https://nlp.johnsnowlabs.com/docs/en/jsl/streamlit_viz_examples) * The complete list of all 4000+ models & pipelines in 200+ languages is available on [Models Hub](https://nlp.johnsnowlabs.com/models). * [Spark NLP publications](https://medium.com/spark-nlp) -* [NLU in Action](https://nlp.johnsnowlabs.com/demo) +* [NLU in Action](https://nlp.johnsnowlabs.com/demos) * [NLU documentation](https://nlp.johnsnowlabs.com/docs/en/jsl/install) * [Discussions](https://github.com/JohnSnowLabs/spark-nlp/discussions) Engage with other community members, share ideas, and show off how you use Spark NLP and NLU! @@ -4093,7 +4093,7 @@ See https://nlp.johnsnowlabs.com/2021/03/31/jsl_ner_wip_clinical_en.html for mor * [Streamlit visualizations docs](https://nlp.johnsnowlabs.com/docs/en/jsl/streamlit_viz_examples) * The complete list of all 4000+ models & pipelines in 200+ languages is available on [Models Hub](https://nlp.johnsnowlabs.com/models). * [Spark NLP publications](https://medium.com/spark-nlp) -* [NLU in Action](https://nlp.johnsnowlabs.com/demo) +* [NLU in Action](https://nlp.johnsnowlabs.com/demos) * [NLU documentation](https://nlp.johnsnowlabs.com/docs/en/jsl/install) * [Discussions](https://github.com/JohnSnowLabs/spark-nlp/discussions) Engage with other community members, share ideas, and show off how you use Spark NLP and NLU! @@ -6244,7 +6244,7 @@ In the following table the NLU and Spark-NLP references are listed: * [Streamlit visualizations docs](https://nlp.johnsnowlabs.com/docs/en/jsl/streamlit_viz_examples) * The complete list of all 1100+ models & pipelines in 192+ languages is available on [Models Hub](https://nlp.johnsnowlabs.com/models). * [Spark NLP publications](https://medium.com/spark-nlp) -* [NLU in Action](https://nlp.johnsnowlabs.com/demo) +* [NLU in Action](https://nlp.johnsnowlabs.com/demos) * [NLU documentation](https://nlp.johnsnowlabs.com/docs/en/jsl/install) * [Discussions](https://github.com/JohnSnowLabs/spark-nlp/discussions) Engage with other community members, share ideas, and show off how you use Spark NLP and NLU! @@ -6696,7 +6696,7 @@ hepatitis, and obesity with a body mass index (BMI) of 33.5 kg/m2, presented wit * [New Streamlit visualizations docs](https://nlp.johnsnowlabs.com/docs/en/jsl/streamlit_viz_examples) * The complete list of all 1100+ models & pipelines in 192+ languages is available on [Models Hub](https://nlp.johnsnowlabs.com/models). * [Spark NLP publications](https://medium.com/spark-nlp) -* [NLU in Action](https://nlp.johnsnowlabs.com/demo) +* [NLU in Action](https://nlp.johnsnowlabs.com/demos) * [NLU documentation](https://nlp.johnsnowlabs.com/docs/en/jsl/install) * [Discussions](https://github.com/JohnSnowLabs/spark-nlp/discussions) Engage with other community members, share ideas, and show off how you use Spark NLP and NLU! @@ -6893,7 +6893,7 @@ All of the [140+ NLU tutorial Notebooks](https://github.com/JohnSnowLabs/nlu/tre * [Updated visualization docs](https://nlp.johnsnowlabs.com/docs/en/jsl/viz_examples) * [Models Hub](https://nlp.johnsnowlabs.com/models) with new models * [Spark NLP publications](https://medium.com/spark-nlp) -* [NLU in Action](https://nlp.johnsnowlabs.com/demo) +* [NLU in Action](https://nlp.johnsnowlabs.com/demos) * [NLU documentation](https://nlp.johnsnowlabs.com/docs/en/jsl/install) * [Discussions](https://github.com/JohnSnowLabs/spark-nlp/discussions) Engage with other community members, share ideas, and show off how you use Spark NLP and NLU!