Babelscape/ner4el

Repository for the paper "Named Entity Recognition for Entity Linking: What Works and What's Next" (EMNLP 2021).

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Experimental

This project helps natural language processing (NLP) researchers and engineers develop better Entity Linking (EL) systems, especially when they don't have millions of labeled training examples. It takes raw text as input and outputs identified entities linked to a knowledge base like Wikipedia. This is for machine learning researchers, NLP practitioners, and data scientists working on information extraction or knowledge graph construction.

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Use this if you need to build an Entity Linking system that performs well even with limited training data by leveraging Named Entity Recognition (NER).

Not ideal if you already have access to vast amounts of labeled data for Entity Linking or are not concerned with low-resource settings.

natural-language-processing entity-linking named-entity-recognition information-extraction knowledge-graph-construction
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Python

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Last pushed

Feb 22, 2022

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