Complex Word Identification as a Sequence Labelling Task

Sian Gooding, Ekaterina Kochmar


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
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
Bibkey:
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)
Copy Citation:
PDF:
https://aclanthology.org/P19-1109.pdf