Coopercoppers/PFN
EMNLP 2021 - A Partition Filter Network for Joint Entity and Relation Extraction
This project helps extract key entities (like people, organizations, or methods) and the relationships between them from unstructured text. It takes a sentence or document as input and outputs a list of identified entities and a list of triples describing the relationships. Anyone who needs to automatically identify and link specific information from large volumes of text, such as researchers, data analysts, or content managers, would find this useful.
175 stars. No commits in the last 6 months.
Use this if you need to automatically identify specific entities and the relationships between them from a wide range of English texts, including scientific papers, news articles, or clinical reports.
Not ideal if your primary need is to handle complex nested relationships or head-overlap entities within a sentence, in which case the PFN-nested version is recommended.
Stars
175
Forks
20
Language
Python
License
MIT
Category
Last pushed
Mar 18, 2024
Commits (30d)
0
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