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    <abstract>This paper presents an open-source toolkit for negation detection. It identifies negation cues and their corresponding scope in either raw or parsed text using maximum-margin classification. The system design draws on best practice from the existing literature on negation detection, aiming for a simple and portable system that still achieves competitive performance. Pre-trained models and experimental results are provided for English.</abstract>
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    <identifier type="doi">10.18653/v1/W17-1810</identifier>
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%0 Conference Proceedings
%T An open-source tool for negation detection: a maximum-margin approach
%A Enger, Martine
%A Velldal, Erik
%A Øvrelid, Lilja
%Y Blanco, Eduardo
%Y Morante, Roser
%Y Saurí, Roser
%S Proceedings of the Workshop Computational Semantics Beyond Events and Roles
%D 2017
%8 April
%I Association for Computational Linguistics
%C Valencia, Spain
%F enger-etal-2017-open
%X This paper presents an open-source toolkit for negation detection. It identifies negation cues and their corresponding scope in either raw or parsed text using maximum-margin classification. The system design draws on best practice from the existing literature on negation detection, aiming for a simple and portable system that still achieves competitive performance. Pre-trained models and experimental results are provided for English.
%R 10.18653/v1/W17-1810
%U https://aclanthology.org/W17-1810
%U https://doi.org/10.18653/v1/W17-1810
%P 64-69

Markdown (Informal)

[An open-source tool for negation detection: a maximum-margin approach](https://aclanthology.org/W17-1810) (Enger et al., SemBEaR 2017)

• An open-source tool for negation detection: a maximum-margin approach (Enger et al., SemBEaR 2017)

ACL

• Martine Enger, Erik Velldal, and Lilja Øvrelid. 2017. An open-source tool for negation detection: a maximum-margin approach. In Proceedings of the Workshop Computational Semantics Beyond Events and Roles, pages 64–69, Valencia, Spain. Association for Computational Linguistics.