The BLCU System in the BEA 2019 Shared Task

Liner Yang, Chencheng Wang


Abstract
This paper describes the BLCU Group submissions to the Building Educational Applications (BEA) 2019 Shared Task on Grammatical Error Correction (GEC). The task is to detect and correct grammatical errors that occurred in essays. We participate in 2 tracks including the Restricted Track and the Unrestricted Track. Our system is based on a Transformer model architecture. We integrate many effective methods proposed in recent years. Such as, Byte Pair Encoding, model ensemble, checkpoints average and spell checker. We also corrupt the public monolingual data to further improve the performance of the model. On the test data of the BEA 2019 Shared Task, our system yields F0.5 = 58.62 and 59.50, ranking twelfth and fourth respectively.
Anthology ID:
W19-4421
Volume:
Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications
Month:
August
Year:
2019
Address:
Florence, Italy
Venues:
ACL | BEA | WS
SIG:
SIGEDU
Publisher:
Association for Computational Linguistics
Note:
Pages:
197–206
Language:
URL:
https://aclanthology.org/W19-4421
DOI:
10.18653/v1/W19-4421
Bibkey:
Cite (ACL):
Liner Yang and Chencheng Wang. 2019. The BLCU System in the BEA 2019 Shared Task. In Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications, pages 197–206, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
The BLCU System in the BEA 2019 Shared Task (Yang & Wang, 2019)
Copy Citation:
PDF:
https://aclanthology.org/W19-4421.pdf
Data
Billion Word BenchmarkCoNLL-2014 Shared Task: Grammatical Error CorrectionFCE