Abstract
This paper examines the usefulness of semantic features based on word alignments for estimating the quality of text simplification. Specifically, we introduce seven types of alignment-based features computed on the basis of word embeddings and paraphrase lexicons. Through an empirical experiment using the QATS dataset, we confirm that we can achieve the state-of-the-art performance only with these features.- Anthology ID:
- I17-2019
- Volume:
- Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)
- Month:
- November
- Year:
- 2017
- Address:
- Taipei, Taiwan
- Editors:
- Greg Kondrak, Taro Watanabe
- Venue:
- IJCNLP
- SIG:
- Publisher:
- Asian Federation of Natural Language Processing
- Note:
- Pages:
- 109–115
- Language:
- URL:
- https://aclanthology.org/I17-2019
- DOI:
- Cite (ACL):
- Tomoyuki Kajiwara and Atsushi Fujita. 2017. Semantic Features Based on Word Alignments for Estimating Quality of Text Simplification. In Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers), pages 109–115, Taipei, Taiwan. Asian Federation of Natural Language Processing.
- Cite (Informal):
- Semantic Features Based on Word Alignments for Estimating Quality of Text Simplification (Kajiwara & Fujita, IJCNLP 2017)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/I17-2019.pdf