MITRE at SemEval-2018 Task 11: Commonsense Reasoning without Commonsense Knowledge
Elizabeth Merkhofer, John Henderson, David Bloom, Laura Strickhart, Guido Zarrella
Abstract
This paper describes MITRE’s participation in SemEval-2018 Task 11: Machine Comprehension using Commonsense Knowledge. The techniques explored range from simple bag-of-ngrams classifiers to neural architectures with varied attention and alignment mechanisms. Logistic regression ties the systems together into an ensemble submitted for evaluation. The resulting system answers reading comprehension questions with 82.27% accuracy.- Anthology ID:
- S18-1181
- 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:
- 1078–1082
- Language:
- URL:
- https://aclanthology.org/S18-1181
- DOI:
- 10.18653/v1/S18-1181
- Cite (ACL):
- Elizabeth Merkhofer, John Henderson, David Bloom, Laura Strickhart, and Guido Zarrella. 2018. MITRE at SemEval-2018 Task 11: Commonsense Reasoning without Commonsense Knowledge. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 1078–1082, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- MITRE at SemEval-2018 Task 11: Commonsense Reasoning without Commonsense Knowledge (Merkhofer et al., SemEval 2018)
- PDF:
- https://preview.aclanthology.org/ml4al-ingestion/S18-1181.pdf