ECNU at SemEval-2018 Task 11: Using Deep Learning Method to Address Machine Comprehension Task

Yixuan Sheng; Man Lan; Yuanbin Wu

doi:10.18653/v1/s18-1175

ECNU at SemEval-2018 Task 11: Using Deep Learning Method to Address Machine Comprehension Task

Yixuan Sheng
, Man Lan^*
, Yuanbin Wu

^*Corresponding author for this work

School of Computer Science and Technology

East China Normal University
Shanghai Key Laboratory of Multidimensional Information Processing

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

2 Scopus citations

Abstract

This paper describes the system we submitted to the Task 11 in SemEval 2018, i.e., Machine Comprehension using Commonsense Knowledge. Given a passage and some questions that each have two candidate answers, this task requires the participate system to select out one answer meet the meaning of original text or commonsense knowledge from the candidate answers. For this task, we use a deep learning method to obtain final predict answer by calculating relevance of choices representations and question-aware document representation.

Original language	English
Title of host publication	NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop
Editors	Marianna Apidianaki, Marianna Apidianaki, Saif M. Mohammad, Jonathan May, Ekaterina Shutova, Steven Bethard, Marine Carpuat
Publisher	Association for Computational Linguistics (ACL)
Pages	1048-1052
Number of pages	5
ISBN (Electronic)	9781948087209
DOIs	https://doi.org/10.18653/v1/s18-1175
State	Published - 2018
Event	12th International Workshop on Semantic Evaluation, SemEval 2018, co-located with the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2018 - New Orleans, United States Duration: 5 Jun 2018 → 6 Jun 2018

Publication series

Name	NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop

Conference

Conference	12th International Workshop on Semantic Evaluation, SemEval 2018, co-located with the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2018
Country/Territory	United States
City	New Orleans
Period	5/06/18 → 6/06/18

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10.18653/v1/s18-1175

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Sheng, Y., Lan, M., & Wu, Y. (2018). ECNU at SemEval-2018 Task 11: Using Deep Learning Method to Address Machine Comprehension Task. In M. Apidianaki, M. Apidianaki, S. M. Mohammad, J. May, E. Shutova, S. Bethard, & M. Carpuat (Eds.), NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop (pp. 1048-1052). (NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s18-1175

Sheng, Yixuan ; Lan, Man ; Wu, Yuanbin. / ECNU at SemEval-2018 Task 11 : Using Deep Learning Method to Address Machine Comprehension Task. NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop. editor / Marianna Apidianaki ; Marianna Apidianaki ; Saif M. Mohammad ; Jonathan May ; Ekaterina Shutova ; Steven Bethard ; Marine Carpuat. Association for Computational Linguistics (ACL), 2018. pp. 1048-1052 (NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop).

@inproceedings{ae3dc6130beb410aa8e763a37fc37f0d,

title = "ECNU at SemEval-2018 Task 11: Using Deep Learning Method to Address Machine Comprehension Task",

abstract = "This paper describes the system we submitted to the Task 11 in SemEval 2018, i.e., Machine Comprehension using Commonsense Knowledge. Given a passage and some questions that each have two candidate answers, this task requires the participate system to select out one answer meet the meaning of original text or commonsense knowledge from the candidate answers. For this task, we use a deep learning method to obtain final predict answer by calculating relevance of choices representations and question-aware document representation.",

author = "Yixuan Sheng and Man Lan and Yuanbin Wu",

note = "Publisher Copyright: {\textcopyright} 2018 Association for Computational Linguistics; 12th International Workshop on Semantic Evaluation, SemEval 2018, co-located with the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2018 ; Conference date: 05-06-2018 Through 06-06-2018",

year = "2018",

doi = "10.18653/v1/s18-1175",

language = "英语",

series = "NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop",

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

pages = "1048--1052",

editor = "Marianna Apidianaki and Marianna Apidianaki and Mohammad, \{Saif M.\} and Jonathan May and Ekaterina Shutova and Steven Bethard and Marine Carpuat",

booktitle = "NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop",

address = "澳大利亚",

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Sheng, Y, Lan, M & Wu, Y 2018, ECNU at SemEval-2018 Task 11: Using Deep Learning Method to Address Machine Comprehension Task. in M Apidianaki, M Apidianaki, SM Mohammad, J May, E Shutova, S Bethard & M Carpuat (eds), NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop. NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop, Association for Computational Linguistics (ACL), pp. 1048-1052, 12th International Workshop on Semantic Evaluation, SemEval 2018, co-located with the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2018, New Orleans, United States, 5/06/18. https://doi.org/10.18653/v1/s18-1175

ECNU at SemEval-2018 Task 11: Using Deep Learning Method to Address Machine Comprehension Task. / Sheng, Yixuan; Lan, Man; Wu, Yuanbin.
NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop. ed. / Marianna Apidianaki; Marianna Apidianaki; Saif M. Mohammad; Jonathan May; Ekaterina Shutova; Steven Bethard; Marine Carpuat. Association for Computational Linguistics (ACL), 2018. p. 1048-1052 (NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop).

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

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AU - Wu, Yuanbin

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AB - This paper describes the system we submitted to the Task 11 in SemEval 2018, i.e., Machine Comprehension using Commonsense Knowledge. Given a passage and some questions that each have two candidate answers, this task requires the participate system to select out one answer meet the meaning of original text or commonsense knowledge from the candidate answers. For this task, we use a deep learning method to obtain final predict answer by calculating relevance of choices representations and question-aware document representation.

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Sheng Y, Lan M, Wu Y. ECNU at SemEval-2018 Task 11: Using Deep Learning Method to Address Machine Comprehension Task. In Apidianaki M, Apidianaki M, Mohammad SM, May J, Shutova E, Bethard S, Carpuat M, editors, NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop. Association for Computational Linguistics (ACL). 2018. p. 1048-1052. (NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop). doi: 10.18653/v1/s18-1175

ECNU at SemEval-2018 Task 11: Using Deep Learning Method to Address Machine Comprehension Task

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