Discourse relation sense classification systems for CoNLL-2016 shared task

Ping Jian; Xiaohan She; Chenwei Zhang; Pengcheng Zhang; Jian Feng

doi:10.18653/v1/k16-2022

Discourse relation sense classification systems for CoNLL-2016 shared task

Ping Jian, Xiaohan She, Chenwei Zhang, Pengcheng Zhang, Jian Feng

School of Computer Science and Technology

Beijing Institute of Technology

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

3 Citations (Scopus)

Abstract

This paper reports the submitted discourse relation classification systems of the language information processing group of Beijing Institute of Technology (BIT) to the CoNLL-2016 shared task. In this work, discriminative methods were employed according to the different characteristics of English and Chinese discourse structures. Additionally, distributed representations were introduced to catch the deep semantic relations. Experiments shows their effectiveness on both English and Chinese tasks.

Original language	English
Title of host publication	Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning
Subtitle of host publication	Shared Task, CoNLL 2016
Publisher	Association for Computational Linguistics (ACL)
Pages	158-163
Number of pages	6
ISBN (Electronic)	1932432663, 9781932432664
DOIs	https://doi.org/10.18653/v1/k16-2022
Publication status	Published - 2016
Event	20th SIGNLL Conference on Computational Natural Language Learning: Shared Task, CoNLL 2016 - Berlin, Germany Duration: 7 Aug 2016 → 12 Aug 2016

Publication series

Name	Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning: Shared Task, CoNLL 2016

Conference

Conference	20th SIGNLL Conference on Computational Natural Language Learning: Shared Task, CoNLL 2016
Country/Territory	Germany
City	Berlin
Period	7/08/16 → 12/08/16

Access to Document

10.18653/v1/k16-2022

Cite this

Jian, P., She, X., Zhang, C., Zhang, P., & Feng, J. (2016). Discourse relation sense classification systems for CoNLL-2016 shared task. In Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning: Shared Task, CoNLL 2016 (pp. 158-163). (Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning: Shared Task, CoNLL 2016). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/k16-2022

Jian, Ping ; She, Xiaohan ; Zhang, Chenwei et al. / Discourse relation sense classification systems for CoNLL-2016 shared task. Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning: Shared Task, CoNLL 2016. Association for Computational Linguistics (ACL), 2016. pp. 158-163 (Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning: Shared Task, CoNLL 2016).

@inproceedings{2852d0ecc25345d19ce8c287579972fd,

title = "Discourse relation sense classification systems for CoNLL-2016 shared task",

abstract = "This paper reports the submitted discourse relation classification systems of the language information processing group of Beijing Institute of Technology (BIT) to the CoNLL-2016 shared task. In this work, discriminative methods were employed according to the different characteristics of English and Chinese discourse structures. Additionally, distributed representations were introduced to catch the deep semantic relations. Experiments shows their effectiveness on both English and Chinese tasks.",

author = "Ping Jian and Xiaohan She and Chenwei Zhang and Pengcheng Zhang and Jian Feng",

note = "Publisher Copyright: {\textcopyright} 2016 Association for Computational Linguistics.; 20th SIGNLL Conference on Computational Natural Language Learning: Shared Task, CoNLL 2016 ; Conference date: 07-08-2016 Through 12-08-2016",

year = "2016",

doi = "10.18653/v1/k16-2022",

language = "English",

series = "Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning: Shared Task, CoNLL 2016",

publisher = "Association for Computational Linguistics (ACL)",

pages = "158--163",

booktitle = "Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning",

address = "United States",

}

Jian, P, She, X, Zhang, C, Zhang, P & Feng, J 2016, Discourse relation sense classification systems for CoNLL-2016 shared task. in Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning: Shared Task, CoNLL 2016. Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning: Shared Task, CoNLL 2016, Association for Computational Linguistics (ACL), pp. 158-163, 20th SIGNLL Conference on Computational Natural Language Learning: Shared Task, CoNLL 2016, Berlin, Germany, 7/08/16. https://doi.org/10.18653/v1/k16-2022

Discourse relation sense classification systems for CoNLL-2016 shared task. / Jian, Ping; She, Xiaohan; Zhang, Chenwei et al.
Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning: Shared Task, CoNLL 2016. Association for Computational Linguistics (ACL), 2016. p. 158-163 (Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning: Shared Task, CoNLL 2016).

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

TY - GEN

T1 - Discourse relation sense classification systems for CoNLL-2016 shared task

AU - Jian, Ping

AU - She, Xiaohan

AU - Zhang, Chenwei

AU - Zhang, Pengcheng

AU - Feng, Jian

PY - 2016

Y1 - 2016

N2 - This paper reports the submitted discourse relation classification systems of the language information processing group of Beijing Institute of Technology (BIT) to the CoNLL-2016 shared task. In this work, discriminative methods were employed according to the different characteristics of English and Chinese discourse structures. Additionally, distributed representations were introduced to catch the deep semantic relations. Experiments shows their effectiveness on both English and Chinese tasks.

AB - This paper reports the submitted discourse relation classification systems of the language information processing group of Beijing Institute of Technology (BIT) to the CoNLL-2016 shared task. In this work, discriminative methods were employed according to the different characteristics of English and Chinese discourse structures. Additionally, distributed representations were introduced to catch the deep semantic relations. Experiments shows their effectiveness on both English and Chinese tasks.

UR - http://www.scopus.com/inward/record.url?scp=85040585206&partnerID=8YFLogxK

U2 - 10.18653/v1/k16-2022

DO - 10.18653/v1/k16-2022

M3 - Conference contribution

AN - SCOPUS:85040585206

T3 - Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning: Shared Task, CoNLL 2016

SP - 158

EP - 163

BT - Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning

PB - Association for Computational Linguistics (ACL)

T2 - 20th SIGNLL Conference on Computational Natural Language Learning: Shared Task, CoNLL 2016

Y2 - 7 August 2016 through 12 August 2016

ER -

Jian P, She X, Zhang C, Zhang P, Feng J. Discourse relation sense classification systems for CoNLL-2016 shared task. In Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning: Shared Task, CoNLL 2016. Association for Computational Linguistics (ACL). 2016. p. 158-163. (Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning: Shared Task, CoNLL 2016). doi: 10.18653/v1/k16-2022

Discourse relation sense classification systems for CoNLL-2016 shared task

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Cite this