Abstract
Narrative Question Answering is an important task for evaluating and improving reading comprehension abilities in both humans and machines. However, there is a lack of consensus on the skill taxonomy that would enable systematic and comprehensive assessment and learning of the various aspects of Narrative Question Answering. Existing task-level skill views oversimplify the multidimensional nature of tasks, while question-level taxonomies face issues in evaluation and methodology. To address these challenges, we introduce a more inclusive skill taxonomy that synthesizes and redefines narrative understanding skills from previous taxonomies and includes a generation skill dimension from the answering perspective.- Anthology ID:
- 2024.naacl-short.73
- Volume:
- Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 2: Short Papers)
- Month:
- June
- Year:
- 2024
- Address:
- Mexico City, Mexico
- Editors:
- Kevin Duh, Helena Gomez, Steven Bethard
- Venue:
- NAACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 814–820
- Language:
- URL:
- https://aclanthology.org/2024.naacl-short.73
- DOI:
- Cite (ACL):
- Emil Kalbaliyev and Kairit Sirts. 2024. On Narrative Question Answering Skills. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 2: Short Papers), pages 814–820, Mexico City, Mexico. Association for Computational Linguistics.
- Cite (Informal):
- On Narrative Question Answering Skills (Kalbaliyev & Sirts, NAACL 2024)
- PDF:
- https://preview.aclanthology.org/corrections-2024-07/2024.naacl-short.73.pdf