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    <abstract>Temporal relation classification is becoming an active research field. Lots of methods have been proposed, while most of them focus on extracting features from external resources. Less attention has been paid to a significant advance in a closely related task: relation extraction. In this work, we borrow a state-of-the-art method in relation extraction by adopting bidirectional long short-term memory (Bi-LSTM) along dependency paths (DP). We make a “common root” assumption to extend DP representations of cross-sentence links. In the final comparison to two state-of-the-art systems on TimeBank-Dense, our model achieves comparable performance, without using external knowledge, as well as manually annotated attributes of entities (class, tense, polarity, etc.).</abstract>
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%0 Conference Proceedings
%T Classifying Temporal Relations by Bidirectional LSTM over Dependency Paths
%A Cheng, Fei
%A Miyao, Yusuke
%Y Barzilay, Regina
%Y Kan, Min-Yen
%S Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
%D 2017
%8 July
%I Association for Computational Linguistics
%C Vancouver, Canada
%F cheng-miyao-2017-classifying
%X Temporal relation classification is becoming an active research field. Lots of methods have been proposed, while most of them focus on extracting features from external resources. Less attention has been paid to a significant advance in a closely related task: relation extraction. In this work, we borrow a state-of-the-art method in relation extraction by adopting bidirectional long short-term memory (Bi-LSTM) along dependency paths (DP). We make a “common root” assumption to extend DP representations of cross-sentence links. In the final comparison to two state-of-the-art systems on TimeBank-Dense, our model achieves comparable performance, without using external knowledge, as well as manually annotated attributes of entities (class, tense, polarity, etc.).
%R 10.18653/v1/P17-2001
%U https://aclanthology.org/P17-2001
%U https://doi.org/10.18653/v1/P17-2001
%P 1-6

Markdown (Informal)

[Classifying Temporal Relations by Bidirectional LSTM over Dependency Paths](https://aclanthology.org/P17-2001) (Cheng & Miyao, ACL 2017)

• Classifying Temporal Relations by Bidirectional LSTM over Dependency Paths (Cheng & Miyao, ACL 2017)

ACL

• Fei Cheng and Yusuke Miyao. 2017. Classifying Temporal Relations by Bidirectional LSTM over Dependency Paths. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 1–6, Vancouver, Canada. Association for Computational Linguistics.