Yang, H. orcid.org/0000-0002-3372-4801, de Roeck, A., Willis, A. et al. (1 more author) (2010) A Methodology for Automatic Identification of Nocuous Ambiguity. In: Proceedins of The 23th International Conference on Computational Linguistics (Coling’10). The 23th International Conference on Computational Linguistics (Coling’10), 23-27 Aug 2010, Beijing, China. Association for Computational Linguistics , Stroudsburg, PA, USA , pp. 1218-1226.
Abstract
Nocuous ambiguity occurs when a linguistic expression is interpreted differently by different readers in a given context. We present an approach to automatically identify nocuous ambiguity that is likely to lead to misunderstandings among readers. Our model is built on a machine learning architecture. It learns from a set of heuristics each of which predicts a factor that may lead a reader to favor a particular interpretation. An ambiguity threshold indicates the extent to which ambiguity can be tolerated in the application domain. Collections of human judgments are used to train heuristics and set ambiguity thresholds, and for evaluation. We report results from applying the methodology to coordination and anaphora ambiguity. Results show that the method can identify nocuous ambiguity in text, and may be widened to cover further types of ambiguity. We discuss approaches to evaluation.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | ©2010 Association for Computational Linguistics. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 14 Jul 2017 11:10 |
Last Modified: | 19 Dec 2022 13:35 |
Status: | Published |
Publisher: | Association for Computational Linguistics |
Refereed: | Yes |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:110483 |