Does syntax help discourse segmentation? Not so much

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Standard

Does syntax help discourse segmentation? Not so much. / Braud, Chloé Elodie; Lacroix, Ophélie; Søgaard, Anders.

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2017. p. 2432–2442.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Harvard

Braud, CE, Lacroix, O & Søgaard, A 2017, Does syntax help discourse segmentation? Not so much. in Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, pp. 2432–2442, 2017 Conference on Empirical Methods in Natural Language Processing, Copemhagen, Denmark, 09/09/2017. <http://aclweb.org/anthology/D17-1258>

APA

Braud, C. E., Lacroix, O., & Søgaard, A. (2017). Does syntax help discourse segmentation? Not so much. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing (pp. 2432–2442). Association for Computational Linguistics. http://aclweb.org/anthology/D17-1258

Vancouver

Braud CE, Lacroix O, Søgaard A. Does syntax help discourse segmentation? Not so much. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics. 2017. p. 2432–2442

Author

Braud, Chloé Elodie ; Lacroix, Ophélie ; Søgaard, Anders. / Does syntax help discourse segmentation? Not so much. Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2017. pp. 2432–2442

Bibtex

@inproceedings{d6624c58aae942179f05255ae34e8b62,
title = "Does syntax help discourse segmentation? Not so much",
abstract = "Discourse segmentation is the first step inbuilding discourse parsers. Most work ondiscourse segmentation does not scale toreal-world discourse parsing across languages,for two reasons: (i) models relyon constituent trees, and (ii) experimentshave relied on gold standard identificationof sentence and token boundaries. Wetherefore investigate to what extent constituentscan be replaced with universal dependencies,or left out completely, as wellas how state-of-the-art segmenters fare inthe absence of sentence boundaries. Ourresults show that dependency informationis less useful than expected, but we providea fully scalable, robust model thatonly relies on part-of-speech information,and show that it performs well across languagesin the absence of any gold-standardannotation.",
author = "Braud, {Chlo{\'e} Elodie} and Oph{\'e}lie Lacroix and Anders S{\o}gaard",
year = "2017",
language = "English",
isbn = "978-1-945626-97-5",
pages = "2432–2442",
booktitle = "Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing",
publisher = "Association for Computational Linguistics",
note = "2017 Conference on Empirical Methods in Natural Language Processing, EMNLP 2017 ; Conference date: 09-09-2017 Through 11-09-2017",

}

RIS

TY - GEN

T1 - Does syntax help discourse segmentation? Not so much

AU - Braud, Chloé Elodie

AU - Lacroix, Ophélie

AU - Søgaard, Anders

PY - 2017

Y1 - 2017

N2 - Discourse segmentation is the first step inbuilding discourse parsers. Most work ondiscourse segmentation does not scale toreal-world discourse parsing across languages,for two reasons: (i) models relyon constituent trees, and (ii) experimentshave relied on gold standard identificationof sentence and token boundaries. Wetherefore investigate to what extent constituentscan be replaced with universal dependencies,or left out completely, as wellas how state-of-the-art segmenters fare inthe absence of sentence boundaries. Ourresults show that dependency informationis less useful than expected, but we providea fully scalable, robust model thatonly relies on part-of-speech information,and show that it performs well across languagesin the absence of any gold-standardannotation.

AB - Discourse segmentation is the first step inbuilding discourse parsers. Most work ondiscourse segmentation does not scale toreal-world discourse parsing across languages,for two reasons: (i) models relyon constituent trees, and (ii) experimentshave relied on gold standard identificationof sentence and token boundaries. Wetherefore investigate to what extent constituentscan be replaced with universal dependencies,or left out completely, as wellas how state-of-the-art segmenters fare inthe absence of sentence boundaries. Ourresults show that dependency informationis less useful than expected, but we providea fully scalable, robust model thatonly relies on part-of-speech information,and show that it performs well across languagesin the absence of any gold-standardannotation.

M3 - Article in proceedings

SN - 978-1-945626-97-5

SP - 2432

EP - 2442

BT - Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing

PB - Association for Computational Linguistics

T2 - 2017 Conference on Empirical Methods in Natural Language Processing

Y2 - 9 September 2017 through 11 September 2017

ER -

ID: 195014956