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Reference-less Measure of Faithfulness for Grammatical Error Correction

Leshem Choshen, Omri Abend


Abstract
We propose USim, a semantic measure for Grammatical Error Correction (that measures the semantic faithfulness of the output to the source, thereby complementing existing reference-less measures (RLMs) for measuring the output’s grammaticality. USim operates by comparing the semantic symbolic structure of the source and the correction, without relying on manually-curated references. Our experiments establish the validity of USim, by showing that the semantic structures can be consistently applied to ungrammatical text, that valid corrections obtain a high USim similarity score to the source, and that invalid corrections obtain a lower score.
Anthology ID:
N18-2020
Volume:
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Editors:
Marilyn Walker, Heng Ji, Amanda Stent
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
124–129
Language:
URL:
https://aclanthology.org/N18-2020
DOI:
10.18653/v1/N18-2020
Bibkey:
Cite (ACL):
Leshem Choshen and Omri Abend. 2018. Reference-less Measure of Faithfulness for Grammatical Error Correction. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers), pages 124–129, New Orleans, Louisiana. Association for Computational Linguistics.
Cite (Informal):
Reference-less Measure of Faithfulness for Grammatical Error Correction (Choshen & Abend, NAACL 2018)
Copy Citation:
PDF:
https://aclanthology.org/N18-2020.pdf
Note:
 N18-2020.Notes.pdf
Code
 borgr/USim