Semantic Features Based on Word Alignments for Estimating Quality of Text Simplification

Tomoyuki Kajiwara, Atsushi Fujita


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
Venue:
IJCNLP
SIG:
Publisher:
Asian Federation of Natural Language Processing
Note:
Pages:
109–115
Language:
URL:
https://www.aclweb.org/anthology/I17-2019
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/I17-2019.pdf