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

neural-network

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Jupyter Notebook Language

mit License

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$111.5K

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$215.7K

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8 data points · 2021-08-01 → 2026-04-01

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What is the Sshanu/Relation-Classification-using-Bidirectional-LSTM-Tree GitHub project? Description: "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". Written in Jupyter Notebook. Explain what it does, its main use cases, key features, and who would benefit from using it.

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