Title
Data-driven sentence simplification: Survey and benchmark
Date Issued
01 January 2020
Access level
open access
Resource Type
journal article
Author(s)
University of Sheffield
Publisher(s)
MIT Press Journals
Abstract
Sentence Simplification (SS) aims to modify a sentence in order to make it easier to read and understand. In order to do so, several rewriting transformations can be performed such as replacement, reordering, and splitting. Executing these transformations while keeping sentences grammatical, preserving their main idea, and generating simpler output, is a challenging and still far from solved problem. In this article, we survey research on SS, focusing on approaches that attempt to learn how to simplify using corpora of aligned original-simplified sentence pairs in English, which is the dominant paradigm nowadays. We also include a benchmark of different approaches on common data sets so as to compare them and highlight their strengths and limitations. We expect that this survey will serve as a starting point for researchers interested in the task and help spark new ideas for future developments.
Start page
135
End page
187
Volume
46
Issue
1
Language
English
OCDE Knowledge area
Lingüística
Ciencias de la computación
Scopus EID
2-s2.0-85083081608
Source
Computational Linguistics
ISSN of the container
08912017
Sources of information:
Directorio de Producción Científica
Scopus