Abstract
Complex Word Identification (CWI) is concerned with detection of words in need of simplification and is a crucial first step in a simplification pipeline. It has been shown that reliable CWI systems considerably improve text simplification. However, most CWI systems to date address the task on a word-by-word basis, not taking the context into account. In this paper, we present a novel approach to CWI based on sequence modelling. Our system is capable of performing CWI in context, does not require extensive feature engineering and outperforms state-of-the-art systems on this task.- Anthology ID:
- P19-1109
- Volume:
- Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
- Month:
- July
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Anna Korhonen, David Traum, Lluís Màrquez
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1148–1153
- Language:
- URL:
- https://aclanthology.org/P19-1109
- DOI:
- 10.18653/v1/P19-1109
- Cite (ACL):
- Sian Gooding and Ekaterina Kochmar. 2019. Complex Word Identification as a Sequence Labelling Task. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 1148–1153, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Complex Word Identification as a Sequence Labelling Task (Gooding & Kochmar, ACL 2019)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-5/P19-1109.pdf