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
- 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)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/S18-1172.pdf