Comparative judgments are more consistent than binary classification for labelling word complexity
Sian Gooding, Ekaterina Kochmar, Advait Sarkar, Alan Blackwell
Abstract
Lexical simplification systems replace complex words with simple ones based on a model of which words are complex in context. We explore how users can help train complex word identification models through labelling more efficiently and reliably. We show that using an interface where annotators make comparative rather than binary judgments leads to more reliable and consistent labels, and explore whether comparative judgments may provide a faster way for collecting labels.- Anthology ID:
- W19-4024
- Volume:
- Proceedings of the 13th Linguistic Annotation Workshop
- Month:
- August
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Annemarie Friedrich, Deniz Zeyrek, Jet Hoek
- Venue:
- LAW
- SIG:
- SIGANN
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 208–214
- Language:
- URL:
- https://aclanthology.org/W19-4024
- DOI:
- 10.18653/v1/W19-4024
- Cite (ACL):
- Sian Gooding, Ekaterina Kochmar, Advait Sarkar, and Alan Blackwell. 2019. Comparative judgments are more consistent than binary classification for labelling word complexity. In Proceedings of the 13th Linguistic Annotation Workshop, pages 208–214, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Comparative judgments are more consistent than binary classification for labelling word complexity (Gooding et al., LAW 2019)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/W19-4024.pdf