ELiRF-UPV at SemEval-2018 Task 11: Machine Comprehension using Commonsense Knowledge

José-Ángel González, Lluís-F. Hurtado, Encarna Segarra, Ferran Pla


Abstract
This paper describes the participation of ELiRF-UPV team at task 11, Machine Comprehension using Commonsense Knowledge, of SemEval-2018. Our approach is based on the use of word embeddings, NumberBatch Embeddings, and a Deep Learning architecture to find the best answer for the multiple-choice questions based on the narrative text. The results obtained are in line with those obtained by the other participants and they encourage us to continue working on this problem.
Anthology ID:
S18-1172
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:
1034–1037
Language:
URL:
https://aclanthology.org/S18-1172
DOI:
10.18653/v1/S18-1172
Bibkey:
Cite (ACL):
José-Ángel González, Lluís-F. Hurtado, Encarna Segarra, and Ferran Pla. 2018. ELiRF-UPV at SemEval-2018 Task 11: Machine Comprehension using Commonsense Knowledge. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 1034–1037, New Orleans, Louisiana. Association for Computational Linguistics.
Cite (Informal):
ELiRF-UPV at SemEval-2018 Task 11: Machine Comprehension using Commonsense Knowledge (González et al., SemEval 2018)
Copy Citation:
PDF:
https://aclanthology.org/S18-1172.pdf