GIST at SemEval-2018 Task 12: A network transferring inference knowledge to Argument Reasoning Comprehension task

HongSeok Choi, Hyunju Lee


Abstract
This paper describes our GIST team system that participated in SemEval-2018 Argument Reasoning Comprehension task (Task 12). Here, we address two challenging factors: unstated common senses and two lexically close warrants that lead to contradicting claims. A key idea for our system is full use of transfer learning from the Natural Language Inference (NLI) task to this task. We used Enhanced Sequential Inference Model (ESIM) to learn the NLI dataset. We describe how to use ESIM for transfer learning to choose correct warrant through a proposed system. We show comparable results through ablation experiments. Our system ranked 1st among 22 systems, outperforming all the systems more than 10%.
Anthology ID:
S18-1122
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:
773–777
Language:
URL:
https://aclanthology.org/S18-1122
DOI:
10.18653/v1/S18-1122
Bibkey:
Cite (ACL):
HongSeok Choi and Hyunju Lee. 2018. GIST at SemEval-2018 Task 12: A network transferring inference knowledge to Argument Reasoning Comprehension task. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 773–777, New Orleans, Louisiana. Association for Computational Linguistics.
Cite (Informal):
GIST at SemEval-2018 Task 12: A network transferring inference knowledge to Argument Reasoning Comprehension task (Choi & Lee, SemEval 2018)
Copy Citation:
PDF:
https://aclanthology.org/S18-1122.pdf
Code
 hongking9/SemEval-2018-task12
Data
MultiNLISNLI