Textpipe: clean and extract metadata from text
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Updated
Jun 9, 2021 - Python
Textpipe: clean and extract metadata from text
Open Source REST API for named entity extraction, named entity linking, named entity disambiguation, recommendation & reconciliation of entities like persons, organizations and places for (semi)automatic semantic tagging & analysis of documents by linked data knowledge graph like SKOS thesaurus, RDF ontology, database(s) or list(s) of names
Kyoto University Web Document Leads Corpus
General Architecture for Text Engineering
Zero-Shot Open Entity Typing as Type-Compatible Grounding, EMNLP'18.
Code for ACL '19 paper: Towards Improving Neural Named Entity Recognition with Gazetteers
This is a prototype of a multi-lingual suite for named-entity recognition in Python.
Annotated Fuman Kaitori Center Corpus
Named-Entity Recognition for Norwegian Bokmål and Nynorsk
Entity linker for the newspaper collection of the National Library of the Netherlands. Links named entity mentions to DBpedia descriptions using either a binary SVM classifier or a neural net.
Web interface to manually annotate named entity mentions in newspaper articles with the correct DBpedia link(s), if any. Produces labeled data sets for training and evaluating the DAC Entity Linker.
custom models for named-entity recognition
Named Entity Resolution, Extraction, and Linking of Lexically Similar Names
Summarize documents based on content extracted via Rosette API
An improved tool for named entity recognition for Polish based on deep learning.
Post processing for speech recognition
Named Entity Recognition for Real Estate Text | COL772 (NLP) @ IIT Delhi
A Reference Training Corpus of Serbian
Entity Linking on a collection of web pages
Text miner for PubMed abstracts
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