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

Yixuan Sheng, Man Lan, Yuanbin Wu


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.
Anthology ID:
S18-1175
Volume:
Proceedings of the 12th International Workshop on Semantic Evaluation
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Editors:
Marianna Apidianaki, Saif M. Mohammad, Jonathan May, Ekaterina Shutova, Steven Bethard, Marine Carpuat
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
1048–1052
Language:
URL:
https://aclanthology.org/S18-1175
DOI:
10.18653/v1/S18-1175
Bibkey:
Cite (ACL):
Yixuan Sheng, Man Lan, and Yuanbin Wu. 2018. ECNU at SemEval-2018 Task 11: Using Deep Learning Method to Address Machine Comprehension Task. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 1048–1052, New Orleans, Louisiana. Association for Computational Linguistics.
Cite (Informal):
ECNU at SemEval-2018 Task 11: Using Deep Learning Method to Address Machine Comprehension Task (Sheng et al., SemEval 2018)
Copy Citation:
PDF:
https://aclanthology.org/S18-1175.pdf