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A7׳ta: Data on a monolingual Arabic parallel corpus for grammar checking.

Nora Madi1, Hend S Al-Khalifa1

  • 1Department of Information Technology, College of Computer & Information Sciences, King Saud University, Riyadh, Saudi Arabia.

Data in Brief
|December 29, 2018
PubMed
Summary

This study introduces A7׳ta, a new Arabic parallel corpus for grammar error correction. This resource aids in developing Natural Language Processing (NLP) models for improved Arabic grammar checking.

Keywords:
Arabic languageError checkingNLPParallel corpus

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Area of Science:

  • Computational Linguistics
  • Natural Language Processing
  • Corpus Linguistics

Background:

  • Grammar error correction is often framed as a translation task, utilizing Statistical Machine Translation (SMT) or Neural Machine Translation (NMT).
  • Training SMT or NMT models for grammar correction necessitates specialized monolingual parallel corpora.

Purpose of the Study:

  • To present A7׳ta, a novel monolingual parallel corpus of Arabic text specifically designed for grammar error correction.
  • To expand the availability of Arabic error correction resources and facilitate the development of advanced NLP tools.

Main Methods:

  • A corpus of 470 erroneous Arabic sentences and their 470 corresponding error-free versions was manually compiled.
  • Sentences were sourced from a guide on correct Arabic grammar and linguistic usage.
  • Detailed error specifications were provided, leveraging the expertise of language specialists.

Main Results:

  • The A7׳ta corpus comprises 470 parallel sentence pairs, offering a valuable resource for Arabic NLP.
  • This corpus is suitable for training sequence-to-sequence models for Arabic grammar checking tasks.

Conclusions:

  • A7׳ta represents a significant contribution to the field of Arabic Natural Language Processing (NLP).
  • The availability of this corpus will empower researchers and developers to create more effective Arabic grammar correction systems.