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    <titleInfo>
        <title>Detecting negation scope is easy, except when it isn’t</title>
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        <namePart type="given">Federico</namePart>
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    <name type="personal">
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        <namePart type="family">Webber</namePart>
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    <name type="personal">
        <namePart type="given">Hangfeng</namePart>
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            <namePart type="given">Mirella</namePart>
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            <namePart type="given">Phil</namePart>
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    <abstract>Several corpora have been annotated with negation scope—the set of words whose meaning is negated by a cue like the word “not”—leading to the development of classifiers that detect negation scope with high accuracy. We show that for nearly all of these corpora, this high accuracy can be attributed to a single fact: they frequently annotate negation scope as a single span of text delimited by punctuation. For negation scopes not of this form, detection accuracy is low and under-sampling the easy training examples does not substantially improve accuracy. We demonstrate that this is partly an artifact of annotation guidelines, and we argue that future negation scope annotation efforts should focus on these more difficult cases.</abstract>
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%0 Conference Proceedings
%T Detecting negation scope is easy, except when it isn’t
%A Fancellu, Federico
%A Lopez, Adam
%A Webber, Bonnie
%A He, Hangfeng
%Y Lapata, Mirella
%Y Blunsom, Phil
%Y Koller, Alexander
%S Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers
%D 2017
%8 April
%I Association for Computational Linguistics
%C Valencia, Spain
%F fancellu-etal-2017-detecting
%X Several corpora have been annotated with negation scope—the set of words whose meaning is negated by a cue like the word “not”—leading to the development of classifiers that detect negation scope with high accuracy. We show that for nearly all of these corpora, this high accuracy can be attributed to a single fact: they frequently annotate negation scope as a single span of text delimited by punctuation. For negation scopes not of this form, detection accuracy is low and under-sampling the easy training examples does not substantially improve accuracy. We demonstrate that this is partly an artifact of annotation guidelines, and we argue that future negation scope annotation efforts should focus on these more difficult cases.
%U https://aclanthology.org/E17-2010
%P 58-63

Markdown (Informal)

[Detecting negation scope is easy, except when it isn’t](https://aclanthology.org/E17-2010) (Fancellu et al., EACL 2017)

• Detecting negation scope is easy, except when it isn’t (Fancellu et al., EACL 2017)

ACL

• Federico Fancellu, Adam Lopez, Bonnie Webber, and Hangfeng He. 2017. Detecting negation scope is easy, except when it isn’t. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, pages 58–63, Valencia, Spain. Association for Computational Linguistics.