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Using parse features for preposition selection and error detection

Tetreault, Joel, Foster, Jennifer ORCID: 0000-0002-7789-4853 and Chodorow, Martin (2010) Using parse features for preposition selection and error detection. In: ACL 2010 - 48th Annual Meeting of the Association for Computational Linguistics, 11-16 July 2010, Uppsala, Sweden.

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Abstract

We evaluate the effect of adding parse features to a leading model of preposition usage. Results show a significant improvement in the preposition selection task on native speaker text and a modest increment in precision and recall in an ESL error detection task. Analysis of the parser output indicates that it is robust enough in the face of noisy non-native writing to extract useful information.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Subjects:Computer Science > Computational linguistics
DCU Faculties and Centres:Research Initiatives and Centres > National Centre for Language Technology (NCLT)
Published in: Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics. . Association for Computational Linguistics.
Publisher:Association for Computational Linguistics
Official URL:http://www.aclweb.org/anthology/P/P10/
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:15989
Deposited On:08 Dec 2010 12:55 by Shane Harper . Last Modified 10 Oct 2018 15:14

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