Extremely-Fine-Grained-Entity-Typing

PyTorch implementation of our paper "Imposing Label-Relational Inductive Bias for Extremely Fine-Grained Entity Typing" (NAACL19)

natural-language-processing

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90 Stars

8 Forks

90 Watchers

Python Language

mit License

Cost to Build

$12.8K

Market Value

$19.9K

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Growth over time

6 data points · 2021-08-01 → 2023-03-01

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What is the xwhan/Extremely-Fine-Grained-Entity-Typing GitHub project? Description: "PyTorch implementation of our paper "Imposing Label-Relational Inductive Bias for Extremely Fine-Grained Entity Typing" (NAACL19)". Written in Python. Explain what it does, its main use cases, key features, and who would benefit from using it.

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