Sshanu/Relation-Classification-using-Bidirectional-LSTM-Tree
TensorFlow Implementation of the paper "End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures" and "Classifying Relations via Long Short Term Memory Networks along Shortest Dependency Paths" for classifying relations
This project helps you automatically identify and categorize the relationships between specific items or people mentioned in text documents. You provide raw text with identified entities (like names, places, or organizations), and it outputs the categorized relationships between them. This is useful for researchers, intelligence analysts, or anyone who needs to extract structured insights from large volumes of unstructured text.
189 stars. No commits in the last 6 months.
Use this if you need to precisely classify the nature of connections between entities mentioned within sentences, such as 'person works for organization' or 'drug treats disease'.
Not ideal if you primarily need to extract the entities themselves without categorizing their relationships, or if you are working with highly structured data.
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MIT
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Apr 15, 2019
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