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Noun classification from predicate-argument structures

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Hindle, Donald·1990·Proceedings of the 28th annual meeting on Association for Computational Linguistics -

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.

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Metadata

Authors
Hindle, D.
Venue
Proceedings of the 28th annual meeting on Association for Computational Linguistics -
Published
1990
Pages
268-275
OpenAlex
W2123084125
Cited by
545
References
0
FWCI
16.61
Type
conference paper
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Noun classification from predicate-argument structures. https://app.cochat.ai/papers/10.3115/981823.981857
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Hindle, D. (1990). Noun classification from predicate-argument structures. Proceedings of the 28th annual meeting on Association for Computational Linguistics -. https://doi.org/10.3115/981823.981857

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.