Embedding Time Expressions for Deep Temporal Ordering Models

ACL (1), pp. 4400-4406, 2019.

Cited by: 0|Bibtex|Views14|DOI:https://doi.org/10.18653/v1/p19-1433
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Other Links: dblp.uni-trier.de|arxiv.org

Abstract:

Data-driven models have demonstrated state-of-the-art performance in inferring the temporal ordering of events in text. However, these models often overlook explicit temporal signals, such as dates and time windows. Rule-based methods can be used to identify the temporal links between these time expressions (timexes), but they fail to c...More

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