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        <title>Learning with Structured Representations for Negation Scope Extraction</title>
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    <abstract>We report an empirical study on the task of negation scope extraction given the negation cue. Our key observation is that certain useful information such as features related to negation cue, long-distance dependencies as well as some latent structural information can be exploited for such a task. We design approaches based on conditional random fields (CRF), semi-Markov CRF, as well as latent-variable CRF models to capture such information. Extensive experiments on several standard datasets demonstrate that our approaches are able to achieve better results than existing approaches reported in the literature.</abstract>
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    <identifier type="doi">10.18653/v1/P18-2085</identifier>
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%0 Conference Proceedings
%T Learning with Structured Representations for Negation Scope Extraction
%A Li, Hao
%A Lu, Wei
%Y Gurevych, Iryna
%Y Miyao, Yusuke
%S Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F li-lu-2018-learning
%X We report an empirical study on the task of negation scope extraction given the negation cue. Our key observation is that certain useful information such as features related to negation cue, long-distance dependencies as well as some latent structural information can be exploited for such a task. We design approaches based on conditional random fields (CRF), semi-Markov CRF, as well as latent-variable CRF models to capture such information. Extensive experiments on several standard datasets demonstrate that our approaches are able to achieve better results than existing approaches reported in the literature.
%R 10.18653/v1/P18-2085
%U https://aclanthology.org/P18-2085
%U https://doi.org/10.18653/v1/P18-2085
%P 533-539

Markdown (Informal)

[Learning with Structured Representations for Negation Scope Extraction](https://aclanthology.org/P18-2085) (Li & Lu, ACL 2018)

• Learning with Structured Representations for Negation Scope Extraction (Li & Lu, ACL 2018)

ACL

• Hao Li and Wei Lu. 2018. Learning with Structured Representations for Negation Scope Extraction. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 533–539, Melbourne, Australia. Association for Computational Linguistics.