Paper Info
Title
Learning to simplify sentences using Wikipedia
Abstract
In this paper we examine the sentence simplification problem as an English-to-English translation problem, utilizing a corpus of 137K aligned sentence pairs extracted by aligning English Wikipedia and Simple English Wikipedia. This data set contains the full range of transformation operations including rewording, reordering, insertion and deletion. We introduce a new translation model for text simplification that extends a phrase-based machine translation approach to include phrasal deletion. Evaluated based on three metrics that compare against a human reference (BLEU, word-F1 and SSA) our new approach performs significantly better than two text compression techniques (including T3) and the phrase-based translation system without deletion.
Year
Venue
Keywords
2011
Monolingual@ACL
english-to-english translation problem,phrasal deletion,phrase-based machine translation approach,simple english wikipedia,aligning english wikipedia,sentence pair,phrase-based translation system,new approach,sentence simplification problem,new translation model
Field
DocType
Volume
Text simplification,BLEU,Text compression,Evaluation of machine translation,Computer science,Machine translation,Phrase,Speech recognition,Lexical simplification,Artificial intelligence,Natural language processing,Sentence
Conference
W11-16
Citations 
PageRank 
References 
41
1.36
26
Authors
2
Name
Order
Citations
PageRank
William Coster1852.96
David Kauchak236325.92