@inproceedings{98b78338baf54d01bda46af04f60f018,
title = "Semantic structural evaluation for text simplification",
abstract = "Current measures for evaluating text simplification systems focus on evaluating lexical text aspects, neglecting its structural aspects. In this paper we propose the first measure to address structural aspects of text simplification, called SAMSA. It leverages recent advances in semantic parsing to assess simplification quality by decomposing the input based on its semantic structure and comparing it to the output. SAMSA provides a reference-less automatic evaluation procedure, avoiding the problems that reference-based methods face due to the vast space of valid simplifications for a given sentence. Our human evaluation experiments show both SAMSA's substantial correlation with human judgments, as well as the deficiency of existing reference-based measures in evaluating structural simplification.1.",
author = "Elior Sulem and Omri Abend and Ari Rappoport",
note = "Publisher Copyright: {\textcopyright} 2018 The Association for Computational Linguistics.; 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2018 ; Conference date: 01-06-2018 Through 06-06-2018",
year = "2018",
month = jan,
day = "1",
language = "English",
series = "NAACL HLT 2018 - 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Proceedings of the Conference",
publisher = "Association for Computational Linguistics (ACL)",
pages = "685--696",
booktitle = "Long Papers",
address = "United States",
}