Improving Distant Supervision with Maxpooled Attention and Sentence-Level Supervision

@article{Beltagy2018ImprovingDS,
  title={Improving Distant Supervision with Maxpooled Attention and Sentence-Level Supervision},
  author={Iz Beltagy and Kyle Lo and Waleed Ammar},
  journal={CoRR},
  year={2018},
  volume={abs/1810.12956}
}
We propose an effective multitask learning setup for reducing distant supervision noise by leveraging sentence-level supervision. We show how sentence-level supervision can be used to improve the encoding of individual sentences, and to learn which input sentences are more likely to express the relationship between a pair of entities. We also introduce a novel neural architecture for collecting signals from multiple input sentences, which combines the benefits of attention and maxpooling. The… CONTINUE READING
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