FranxYao/Partially-Observed-TreeCRFs
Implementation of AAAI 21 paper: Nested Named Entity Recognition with Partially Observed TreeCRFs
This project helps natural language processing researchers and developers accurately identify all nested mentions of entities within text. It takes raw text documents, often from specialized domains like biomedical research, and outputs a detailed annotation of every named entity, even when they overlap or are contained within other entities. This is useful for anyone working on information extraction, knowledge graph creation, or advanced text analysis.
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Use this if you need to extract named entities from text where those entities can be nested or overlapping, which is common in complex domains like biomedicine or legal documents.
Not ideal if you only need to identify simple, non-overlapping named entities or if you require an off-the-shelf solution without any model training or fine-tuning.
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Python
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Last pushed
May 11, 2021
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