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        <title>Coordination Boundary Identification with Similarity and Replaceability</title>
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    <abstract>We propose a neural network model for coordination boundary detection. Our method relies on the two common properties - similarity and replaceability in conjuncts - in order to detect both similar pairs of conjuncts and dissimilar pairs of conjuncts. The model improves identification of clause-level coordination using bidirectional RNNs incorporating two properties as features. We show that our model outperforms the existing state-of-the-art methods on the coordination annotated Penn Treebank and Genia corpus without any syntactic information from parsers.</abstract>
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%0 Conference Proceedings
%T Coordination Boundary Identification with Similarity and Replaceability
%A Teranishi, Hiroki
%A Shindo, Hiroyuki
%A Matsumoto, Yuji
%Y Kondrak, Greg
%Y Watanabe, Taro
%S Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
%D 2017
%8 November
%I Asian Federation of Natural Language Processing
%C Taipei, Taiwan
%F teranishi-etal-2017-coordination
%X We propose a neural network model for coordination boundary detection. Our method relies on the two common properties - similarity and replaceability in conjuncts - in order to detect both similar pairs of conjuncts and dissimilar pairs of conjuncts. The model improves identification of clause-level coordination using bidirectional RNNs incorporating two properties as features. We show that our model outperforms the existing state-of-the-art methods on the coordination annotated Penn Treebank and Genia corpus without any syntactic information from parsers.
%U https://aclanthology.org/I17-1027
%P 264-272

Markdown (Informal)

[Coordination Boundary Identification with Similarity and Replaceability](https://aclanthology.org/I17-1027) (Teranishi et al., IJCNLP 2017)

• Coordination Boundary Identification with Similarity and Replaceability (Teranishi et al., IJCNLP 2017)

ACL

• Hiroki Teranishi, Hiroyuki Shindo, and Yuji Matsumoto. 2017. Coordination Boundary Identification with Similarity and Replaceability. In Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 264–272, Taipei, Taiwan. Asian Federation of Natural Language Processing.