Receiling/ENPAR
Code for "ENPAR: Enhancing Entity and Entity Pair Representations for Joint Entity Relation Extraction.", EACL2021. It is based on our NERE toolkit (https://github.com/Receiling/NERE).
This tool helps researchers and data scientists automatically extract entities (like people, places, or organizations) and the relationships between them (e.g., 'works at') from unstructured text. You provide raw text data, and it outputs structured information detailing identified entities and their relationships. This is ideal for those who need to convert large volumes of text into a structured, queryable format for analysis or knowledge base creation.
No commits in the last 6 months.
Use this if you need to automatically identify specific items and how they relate to each other within extensive textual documents, such as research papers, news articles, or reports.
Not ideal if your primary goal is simple keyword extraction or if you only need to identify entities without understanding their relationships, as it's designed for more complex relational extraction.
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Language
Python
License
MIT
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Last pushed
Jun 17, 2022
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