Abstract
We propose USIM, a semantic measure for Grammatical Error Correction (GEC) 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 (1) semantic annotation can be consistently applied to ungrammatical text; (2) valid corrections obtain a high USIM similarity score to the source; and (3) invalid corrections obtain a lower score.
| Original language | English |
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| Title of host publication | Short Papers |
| Publisher | Association for Computational Linguistics (ACL) |
| Pages | 124-129 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781948087292 |
| State | Published - 2018 |
| Event | 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2018 - New Orleans, United States Duration: 1 Jun 2018 → 6 Jun 2018 |
Publication series
| Name | NAACL HLT 2018 - 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Proceedings of the Conference |
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| Volume | 2 |
Conference
| Conference | 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2018 |
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| Country/Territory | United States |
| City | New Orleans |
| Period | 1/06/18 → 6/06/18 |
Bibliographical note
Publisher Copyright:© 2018 Association for Computational Linguistics.