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Using very large corpora to detect raising and control verbs

Chrupała, Grzegorz and van Genabith, Josef (2007) Using very large corpora to detect raising and control verbs. In: Lexical Functional Grammar 2007, 28-30 July 2007, California, USA.

Abstract
The distinction between raising and subject-control verbs, although crucial for the construction of semantics, is not easy to make given access to only the local syntactic configuration of the sentence. In most contexts raising verbs and control verbs display identical superficial syntactic structure. Linguists apply grammaticality tests to distinguish these verb classes. Our idea is to learn to predict the raising-control distinction by simulating such grammaticality judgments by means of pattern searches. Experiments with regression tree models show that using pattern counts from large unannotated corpora can be used to assess how likely a verb form is to appear in raising vs. control constructions. For this task it is beneficial to use the much larger but also noisier Web corpus rather than the smaller and cleaner Gigaword corpus. A similar methodology can be useful for detecting other lexical semantic distinctions: it could be used whenever a test employed to make linguistically interesting distinctions can be reduced to a pattern search in an unannotated corpus.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:lexical functional grammar;
Subjects:Computer Science > Machine translating
DCU Faculties and Centres:Research Initiatives and Centres > National Centre for Language Technology (NCLT)
Published in: Proceedings of the LFG07 Conference. . CSLI Publications.
Publisher:CSLI Publications
Official URL:http://csli-publications.stanford.edu/LFG/12/lfg07...
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland, SFI 04/IN/I527
ID Code:15201
Deposited On:17 Feb 2010 14:16 by DORAS Administrator . Last Modified 19 Jul 2018 14:50
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