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seg's Introduction

SeG

A pytorch implementation of the paper: Self-Attention Enhanced Selective Gate with Entity-Aware Embedding for Distantly Supervised Relation Extraction.

Requirements

  • python==3.8
  • pytorch==1.6
  • numpy==1.19.1
  • tqdm==4.48.2
  • scikit_learn==0.23.2

Data

Download the dataset from here, and unzip it under ./data/.

Train and Test

python main.py

Experimental Result

AUC P@100 P@200 P@300 Mean
0.452 0.810 0.790 0.763 0.772

Note

PCNN and SAN DO NOT share the same entity-aware embedding layer, and the lambda values for PCNN and SAN are 0.05 and 1.0 respectively (confirmed by the authors).

seg's People

Contributors

tmliang avatar

Stargazers

 avatar Quincy avatar

Forkers

quincy1994

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