wenxueru/EntityDetection
Neural Processing Letters: End-to-End Entity Detection with Proposer and Regressor
This tool helps researchers and analysts automatically identify and classify specific terms or "entities" within text documents, even when those entities are nested within each other. You input raw text, such as scientific articles or news reports, and it outputs the text with recognized entities like genes, proteins, or company names highlighted and categorized. It's designed for anyone who needs to extract structured information from unstructured text, particularly in specialized domains like biology or finance.
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Use this if you need to accurately pinpoint and label specific terms, like medical conditions or company names, within large volumes of text, especially when these terms might overlap or be embedded within other entities.
Not ideal if you only need to identify single, non-overlapping keywords or phrases, or if your text analysis tasks don't involve complex, nested information extraction.
Stars
12
Forks
1
Language
Python
License
Apache-2.0
Category
Last pushed
Jun 06, 2023
Commits (30d)
0
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