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        <title>Sentence Boundary Detection on Line Breaks in Japanese</title>
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            <title>Proceedings of the Sixth Workshop on Noisy User-generated Text (W-NUT 2020)</title>
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            <namePart type="given">Wei</namePart>
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    <abstract>For NLP, sentence boundary detection (SBD) is an essential task to decompose a text into sentences. Most of the previous studies have used a simple rule that uses only typical characters as sentence boundaries. However, some characters may or may not be sentence boundaries depending on the context. We focused on line breaks in them. We newly constructed annotated corpora, implemented sentence boundary detectors, and analyzed performance of SBD in several settings.</abstract>
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%0 Conference Proceedings
%T Sentence Boundary Detection on Line Breaks in Japanese
%A Hayashibe, Yuta
%A Mitsuzawa, Kensuke
%Y Xu, Wei
%Y Ritter, Alan
%Y Baldwin, Tim
%Y Rahimi, Afshin
%S Proceedings of the Sixth Workshop on Noisy User-generated Text (W-NUT 2020)
%D 2020
%8 November
%I Association for Computational Linguistics
%C Online
%F hayashibe-mitsuzawa-2020-sentence
%X For NLP, sentence boundary detection (SBD) is an essential task to decompose a text into sentences. Most of the previous studies have used a simple rule that uses only typical characters as sentence boundaries. However, some characters may or may not be sentence boundaries depending on the context. We focused on line breaks in them. We newly constructed annotated corpora, implemented sentence boundary detectors, and analyzed performance of SBD in several settings.
%R 10.18653/v1/2020.wnut-1.10
%U https://aclanthology.org/2020.wnut-1.10
%U https://doi.org/10.18653/v1/2020.wnut-1.10
%P 71-75

Markdown (Informal)

[Sentence Boundary Detection on Line Breaks in Japanese](https://aclanthology.org/2020.wnut-1.10) (Hayashibe & Mitsuzawa, WNUT 2020)

• Sentence Boundary Detection on Line Breaks in Japanese (Hayashibe & Mitsuzawa, WNUT 2020)

ACL

• Yuta Hayashibe and Kensuke Mitsuzawa. 2020. Sentence Boundary Detection on Line Breaks in Japanese. In Proceedings of the Sixth Workshop on Noisy User-generated Text (W-NUT 2020), pages 71–75, Online. Association for Computational Linguistics.