Joint Event and Temporal Relation Extraction with Shared Representations and Structured Prediction

EMNLP/IJCNLP (1), pp. 434-444, 2019.

Cited by: 2|Bibtex|Views23|DOI:https://doi.org/10.18653/v1/D19-1041
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Other Links: academic.microsoft.com|dblp.uni-trier.de|arxiv.org

Abstract:

We propose a joint event and temporal relation extraction model with shared representation learning and structured prediction. The proposed method has two advantages over existing work. First, it improves event representation by allowing the event and relation modules to share the same contextualized embeddings and neural representation...More

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