Sentence alignment methods for improving text simplification systems

Štajner, Sanja ; Franco-Salvador, Mark ; Ponzetto, Simone Paolo ; Rosso, Paolo ; Stuckenschmidt, Heiner

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Document Type: Conference or workshop publication
Year of publication: 2017
Book title: The 55th Annual Meeting of the Association for Computational Linguistics - proceedings of the conference : July 30-August 4, 2017, Vancouver, Canada : ACL 2017
Volume: 2
Page range: 97-102
Conference title: The 55th Annual Meeting of the Association for Computational Linguistics (ACL)
Location of the conference venue: Vancouver, Canada
Date of the conference: July 30 - August 4 2017
Publisher: Barzilay, Regina
Place of publication: Stroudsburg, PA
Publishing house: Association for Computational Linguistics
ISBN: 978-1-945626-76-0
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Publication language: English
Institution: School of Business Informatics and Mathematics > Information Systems III: Enterprise Data Analysis (Ponzetto 2016-)
Außerfakultäre Einrichtungen > SFB 884
School of Business Informatics and Mathematics > Practical Computer Science II: Artificial Intelligence (Stuckenschmidt 2009-)
Subject: 004 Computer science, internet
Keywords (English): automated text simplification , sentence alignment , natural language processing
Abstract: We provide several methods for sentence alignment of texts with different complexity levels. Using the best of them, we sentence-align the Newsela corpora, thus providing large training materials for automatic text simplification (ATS) systems. We show that using this dataset, even the standard phrase-based statistical machine translation models for ATS can outperform the state-of-the-art ATS systems.

Dieser Eintrag ist Teil der Universitätsbibliographie.

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