Noun classification from predicate-argument structures

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Noun classification from predicate-argument structures

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Annual Meeting of the ACL archive
Proceedings of the 28th annual meeting on Association for Computational Linguistics table of contents

Pittsburgh, Pennsylvania

Pages: 268 - 275

Year of Publication: 1990

Author

Donald Hindle

AT&T Bell Laboratories, Murray Hill, NJ

Publisher

Association for Computational Linguistics Morristown, NJ, USA

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Downloads (6 Weeks): 3, Downloads (12 Months): 62, Citation Count: 98

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abstract references cited by collaborative colleagues

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DOI Bookmark:	10.3115/981823.981857

ABSTRACT

A method of determining the similarity of nouns on the basis of a metric derived from the distribution of subject, verb and object in a large text corpus is described. The resulting quasi-semantic classification of nouns demonstrates the plausibility of the distributional hypothesis, and has potential application to a variety of tasks, including automatic indexing, resolving nominal compounds, and determining the scope of modification.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Collaborative Colleagues:

Donald Hindle: colleagues

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