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        <title>Semantic Structural Evaluation for Text Simplification</title>
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        <namePart type="given">Elior</namePart>
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            <namePart type="given">Heng</namePart>
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    <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.</abstract>
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%0 Conference Proceedings
%T Semantic Structural Evaluation for Text Simplification
%A Sulem, Elior
%A Abend, Omri
%A Rappoport, Ari
%Y Walker, Marilyn
%Y Ji, Heng
%Y Stent, Amanda
%S Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F sulem-etal-2018-semantic
%X 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.
%R 10.18653/v1/N18-1063
%U https://aclanthology.org/N18-1063
%U https://doi.org/10.18653/v1/N18-1063
%P 685-696

Markdown (Informal)

[Semantic Structural Evaluation for Text Simplification](https://aclanthology.org/N18-1063) (Sulem et al., NAACL 2018)

• Semantic Structural Evaluation for Text Simplification (Sulem et al., NAACL 2018)

ACL

• Elior Sulem, Omri Abend, and Ari Rappoport. 2018. Semantic Structural Evaluation for Text Simplification. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pages 685–696, New Orleans, Louisiana. Association for Computational Linguistics.