Receiling/UniRE
Source code for "UniRE: A Unified Label Space for Entity Relation Extraction.", ACL2021. It is based on our NERE toolkit (https://github.com/Receiling/NERE).
This project helps natural language processing researchers extract structured information from text by identifying entities (like people or organizations) and the relationships between them (like 'works for' or 'located in'). It takes raw text documents as input and outputs a list of identified entities and their corresponding relationships. NLP researchers or anyone working with information extraction from large text corpora would find this useful.
122 stars. No commits in the last 6 months.
Use this if you are an NLP researcher working on named entity recognition and relation extraction tasks, especially in academic or scientific contexts.
Not ideal if you need a production-ready, user-friendly tool for general information extraction without deep technical expertise in machine learning.
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122
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22
Language
Python
License
MIT
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Last pushed
Apr 13, 2022
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