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Add new metas (#18)
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Add new metas

Co-authored-by: Explosion Bot <contact@explosion.ai>
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ines and explosion-bot committed Sep 27, 2019
2 parents fab7240 + 7433a1f commit c5623d0
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161 changes: 161 additions & 0 deletions meta/de_core_news_md-2.2.0.json
@@ -0,0 +1,161 @@
{
"lang": "de",
"name": "core_news_md",
"license": "MIT",
"author": "Explosion",
"url": "https://explosion.ai",
"email": "contact@explosion.ai",
"sources": [
{
"name": "TIGER Corpus",
"url": "https://www.ims.uni-stuttgart.de/forschung/ressourcen/korpora/tiger.html",
"license": "commercial (licensed by Explosion)"
},
{
"name": "WikiNER",
"url": "https://figshare.com/articles/Learning_multilingual_named_entity_recognition_from_Wikipedia/5462500",
"license": "CC BY 4.0"
}
],
"description": "German multi-task CNN trained on the TIGER and WikiNER corpus. Assigns context-specific token vectors, POS tags, dependency parse and named entities. Supports identification of PER, LOC, ORG and MISC entities.",
"notes": "Because the model is trained on Wikipedia, it may perform inconsistently on many genres, such as social media text. The NER accuracy refers to the \"silver standard\" annotations in the WikiNER corpus. Accuracy on these annotations tends to be higher than correct human annotations.",
"pipeline": [
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],
"version": "2.2.0",
"spacy_version": ">=2.2.0",
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},
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"checksum": "09f79aa1fb1fe2e36ca5172c4b17d824e8d6454b98b2e62fae85de5ec193c1d8"
}
155 changes: 155 additions & 0 deletions meta/de_core_news_sm-2.2.0.json
@@ -0,0 +1,155 @@
{
"lang": "de",
"name": "core_news_sm",
"license": "MIT",
"author": "Explosion",
"url": "https://explosion.ai",
"email": "contact@explosion.ai",
"sources": [
{
"name": "TIGER Corpus",
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"license": "commercial (licensed by Explosion)"
},
{
"name": "WikiNER",
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"license": "CC BY 4.0"
}
],
"description": "German multi-task CNN trained on the TIGER and WikiNER corpus. Assigns context-specific token vectors, POS tags, dependency parse and named entities. Supports identification of PER, LOC, ORG and MISC entities.",
"notes": "Because the model is trained on Wikipedia, it may perform inconsistently on many genres, such as social media text. The NER accuracy refers to the \"silver standard\" annotations in the WikiNER corpus. Accuracy on these annotations tends to be higher than correct human annotations.",
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}

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