luozhouyang/TPLinker
TPLinker: Single-stage Joint Extraction of Entities and Relations Through Token Pair Linking
This project helps natural language processing (NLP) researchers and data scientists automatically extract key information from unstructured text. It takes raw text as input and identifies specific entities (like people, places, or organizations) along with the relationships between them. For instance, it can determine that 'Barack Obama' is 'married to' 'Michelle Obama' from a sentence, making it useful for building knowledge graphs or populating databases.
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Use this if you need to precisely identify both entities and the connections between them from large volumes of text in a single, streamlined process.
Not ideal if you only need to identify entities without their relationships, or if you prefer a multi-stage approach for information extraction.
Stars
18
Forks
5
Language
Python
License
Apache-2.0
Category
Last pushed
Apr 15, 2021
Commits (30d)
0
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