Volume 12, Number 15, September 2022

GRASS: A Syntactic Text Simplification System based on Semantic Representations

  Authors

Rita Hijazi^{1, 2}, Bernard Espinasse¹ and Núria Gala², ¹Aix-Marseille Univ., Laboratoire Informatique et Systèmes (LIS UMR 7020), France, ²Aix-Marseille Univ., Laboratoire Parole et Langage (LPL UMR 7309), France

  Abstract

Automatic Text Simplification (ATS) is the process of reducing a text's linguistic complexity to improve its understandability and readability while maintaining its original information, content, and meaning. Several text transformation operations can be performed such as splitting a sentence into several shorter sentences, substitution of complex elements, and reorganization. It has been shown that the implementation of these operations essentially at a syntactic level causes several problems that could be solved by using semantic representations. In this paper, we present GRASS (GRAph-based Semantic representation for syntactic Simplification), a rulebased automatic syntactic simplification system that uses semantic representations. The system allows the syntactic transformation of complex constructions, such as subordination clauses, appositive clauses, coordination clauses, and passive forms into simpler sentences. It is based on graph-based meaning representation of the text expressed in DMRS (Dependency Minimal Recursion Semantics) notation and it uses rewriting rules. The experimental results obtained on a reference corpus and according to specific metrics outperform the results obtained by other state of the art systems on the same reference corpus.

  Keywords

Syntactic Text Simplification, Graph-Based Meaning Representation, DMRS, Graph-Rewriting.