Combining Distant and Direct Supervision for Neural Relation Extraction

@inproceedings{Beltagy2019CombiningDA,
  title={Combining Distant and Direct Supervision for Neural Relation Extraction},
  author={Iz Beltagy and Kyle Lo and Waleed Ammar},
  booktitle={NAACL-HLT},
  year={2019}
}
In relation extraction with distant supervision, noisy labels make it difficult to train quality models. Previous neural models addressed this problem using an attention mechanism that attends to sentences that are likely to express the relations. We improve such models by combining the distant supervision data with an additional directly-supervised data, which we use as supervision for the attention weights. We find that joint training on both types of supervision leads to a better model… CONTINUE READING
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