Abstract
In a semantic frame resource such as FrameNet, the definition sentence of a frame is essential for humans to understand the meaning of the frame intuitively. Recently, several attempts have been made to induce semantic frames from large corpora, but the cost of creating the definition sentences for such frames is significant. In this paper, we address a new task of generating frame definitions from a set of frame-evoking words. Specifically, given a cluster of frame-evoking words and associated exemplars induced as the same semantic frame, we utilize a large language model to generate frame definitions. We demonstrate that incorporating frame element reasoning as chain-of-thought can enhance the inclusion of correct frame elements in the generated definitions.- Anthology ID:
- 2024.findings-acl.661
- Volume:
- Findings of the Association for Computational Linguistics: ACL 2024
- Month:
- August
- Year:
- 2024
- Address:
- Bangkok, Thailand
- Editors:
- Lun-Wei Ku, Andre Martins, Vivek Srikumar
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 11112–11118
- Language:
- URL:
- https://aclanthology.org/2024.findings-acl.661
- DOI:
- 10.18653/v1/2024.findings-acl.661
- Cite (ACL):
- Yi Han, Ryohei Sasano, and Koichi Takeda. 2024. Definition Generation for Automatically Induced Semantic Frame. In Findings of the Association for Computational Linguistics: ACL 2024, pages 11112–11118, Bangkok, Thailand. Association for Computational Linguistics.
- Cite (Informal):
- Definition Generation for Automatically Induced Semantic Frame (Han et al., Findings 2024)
- PDF:
- https://preview.aclanthology.org/autopr/2024.findings-acl.661.pdf