Learning to Define Terms in the Software Domain
Vidhisha Balachandran, Dheeraj Rajagopal, Rose Catherine Kanjirathinkal, William Cohen
Abstract
One way to test a person’s knowledge of a domain is to ask them to define domain-specific terms. Here, we investigate the task of automatically generating definitions of technical terms by reading text from the technical domain. Specifically, we learn definitions of software entities from a large corpus built from the user forum Stack Overflow. To model definitions, we train a language model and incorporate additional domain-specific information like word co-occurrence, and ontological category information. Our approach improves previous baselines by 2 BLEU points for the definition generation task. Our experiments also show the additional challenges associated with the task and the short-comings of language-model based architectures for definition generation.- Anthology ID:
- W18-6122
- Volume:
- Proceedings of the 2018 EMNLP Workshop W-NUT: The 4th Workshop on Noisy User-generated Text
- Month:
- November
- Year:
- 2018
- Address:
- Brussels, Belgium
- Editors:
- Wei Xu, Alan Ritter, Tim Baldwin, Afshin Rahimi
- Venue:
- WNUT
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 164–172
- Language:
- URL:
- https://aclanthology.org/W18-6122
- DOI:
- 10.18653/v1/W18-6122
- Cite (ACL):
- Vidhisha Balachandran, Dheeraj Rajagopal, Rose Catherine Kanjirathinkal, and William Cohen. 2018. Learning to Define Terms in the Software Domain. In Proceedings of the 2018 EMNLP Workshop W-NUT: The 4th Workshop on Noisy User-generated Text, pages 164–172, Brussels, Belgium. Association for Computational Linguistics.
- Cite (Informal):
- Learning to Define Terms in the Software Domain (Balachandran et al., WNUT 2018)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/W18-6122.pdf