NAIST at 2013 CoNLL Grammatical Error Correction Shared Task

نویسندگان

  • Ippei Yoshimoto
  • Tomoya Kose
  • Kensuke Mitsuzawa
  • Keisuke Sakaguchi
  • Tomoya Mizumoto
  • Yuta Hayashibe
  • Mamoru Komachi
  • Yuji Matsumoto
چکیده

This paper describes the Nara Institute of Science and Technology (NAIST) error correction system in the CoNLL 2013 Shared Task. We constructed three systems: a system based on the Treelet Language Model for verb form and subjectverb agreement errors; a classifier trained on both learner and native corpora for noun number errors; a statistical machine translation (SMT)-based model for preposition and determiner errors. As for subject-verb agreement errors, we show that the Treelet Language Model-based approach can correct errors in which the target verb is distant from its subject. Our system ranked fourth on the official run.

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تاریخ انتشار 2013