The AIP-Tohoku System at the BEA-2019 Shared Task

Hiroki Asano, Masato Mita, Tomoya Mizumoto, Jun Suzuki


Abstract
We introduce the AIP-Tohoku grammatical error correction (GEC) system for the BEA-2019 shared task in Track 1 (Restricted Track) and Track 2 (Unrestricted Track) using the same system architecture. Our system comprises two key components: error generation and sentence-level error detection. In particular, GEC with sentence-level grammatical error detection is a novel and versatile approach, and we experimentally demonstrate that it significantly improves the precision of the base model. Our system is ranked 9th in Track 1 and 2nd in Track 2.
Anthology ID:
W19-4418
Volume:
Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications
Month:
August
Year:
2019
Address:
Florence, Italy
Editors:
Helen Yannakoudakis, Ekaterina Kochmar, Claudia Leacock, Nitin Madnani, Ildikó Pilán, Torsten Zesch
Venue:
BEA
SIG:
SIGEDU
Publisher:
Association for Computational Linguistics
Note:
Pages:
176–182
Language:
URL:
https://aclanthology.org/W19-4418
DOI:
10.18653/v1/W19-4418
Bibkey:
Cite (ACL):
Hiroki Asano, Masato Mita, Tomoya Mizumoto, and Jun Suzuki. 2019. The AIP-Tohoku System at the BEA-2019 Shared Task. In Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications, pages 176–182, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
The AIP-Tohoku System at the BEA-2019 Shared Task (Asano et al., BEA 2019)
Copy Citation:
PDF:
https://aclanthology.org/W19-4418.pdf