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Clustering verbs semantically according to their alternation behaviour

Author:

Sabine Schulte im WaldeAuthors Info & Claims

COLING '00: Proceedings of the 18th conference on Computational linguistics - Volume 2

Pages 747 - 753

https://doi.org/10.3115/992730.992754

Published: 31 July 2000 Publication History

Abstract

Verbs were clustered semantically on the basis of their alternation behaviour, as characterised by their syntactic subcategorisation frames extracted from maximum probability parses of a robust statistical parser, and completed by assigning WordNet classes as selectional preferences to the frame arguments. The clustering was achieved (a) iteratively by measuring the relative entropy between the verbs' probability distributions over the frame types, and (b) by utilising a latent class analysis based on the joint frequencies of verbs and frame types.

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Sabine Schulte im Walde. 1998. Automatic Semantic Classification of Verbs According to Their Alternation Behaviour. Master's thesis, Institut für Maschinelle Sprachverarbeitung, Universität Stuttgart.

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Cited By

Drozd AGladkova AMatsuoka S(2015)Python, performance, and natural language processingProceedings of the 5th Workshop on Python for High-Performance and Scientific Computing10.1145/2835857.2835858(1-10)Online publication date: 15-Nov-2015
https://dl.acm.org/doi/10.1145/2835857.2835858
Shutova EKaplan JTeufel SKorhonen A(2013)A computational model of logical metonymyACM Transactions on Speech and Language Processing 10.1145/2483969.248397310:3(1-28)Online publication date: 11-Jul-2013
https://dl.acm.org/doi/10.1145/2483969.2483973
Hajnicz E(2011)Grouping alternating schemata in semantic valence dictionary of polish verbsProceedings of the 14th international conference on Text, speech and dialogue10.5555/2040037.2040059(155-162)Online publication date: 1-Sep-2011
https://dl.acm.org/doi/10.5555/2040037.2040059
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Clustering verbs semantically according to their alternation behaviour
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cover image DL Hosted proceedings

COLING '00: Proceedings of the 18th conference on Computational linguistics - Volume 2

July 2000

549 pages

Program Chair:
Martin Kay

Sponsors

DFKI: DFKI GmbH
Ministète de la Recherche Français
Deutsche Forschungsgemeinschaft
Loria
Centre Universitaire de Luxembourg
Université Nancy 2
Universität des Saarlandes
Ministerium für Bildung, Kultur und Wissenschaft des Saarlandes

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Association for Computational Linguistics

United States

Publication History

Published: 31 July 2000

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Cited By

Drozd AGladkova AMatsuoka S(2015)Python, performance, and natural language processingProceedings of the 5th Workshop on Python for High-Performance and Scientific Computing10.1145/2835857.2835858(1-10)Online publication date: 15-Nov-2015
https://dl.acm.org/doi/10.1145/2835857.2835858
Shutova EKaplan JTeufel SKorhonen A(2013)A computational model of logical metonymyACM Transactions on Speech and Language Processing 10.1145/2483969.248397310:3(1-28)Online publication date: 11-Jul-2013
https://dl.acm.org/doi/10.1145/2483969.2483973
Hajnicz E(2011)Grouping alternating schemata in semantic valence dictionary of polish verbsProceedings of the 14th international conference on Text, speech and dialogue10.5555/2040037.2040059(155-162)Online publication date: 1-Sep-2011
https://dl.acm.org/doi/10.5555/2040037.2040059
Petasis GKarkaletsis VPaliouras GKrithara AZavitsanos E(2011)Ontology population and enrichmentKnowledge-driven multimedia information extraction and ontology evolution10.5555/2001069.2001075(134-166)Online publication date: 1-Jan-2011
https://dl.acm.org/doi/10.5555/2001069.2001075
Altamirano Ii Alemany LSolorio TPedersen T(2010)IRASubcat, a highly customizable, language independent tool for the acquisition of verbal subcategorization information from corpusProceedings of the NAACL HLT 2010 Young Investigators Workshop on Computational Approaches to Languages of the Americas10.5555/1868701.1868713(84-91)Online publication date: 6-Jun-2010
https://dl.acm.org/doi/10.5555/1868701.1868713
Fukumoto FSuzuki YYamashita K(2009)Polysemous verb classification using subcategorization acquisition and graph-based clusteringProceedings of the 4th conference on Human language technology: challenges for computer science and linguistics10.5555/1987717.1987730(115-126)Online publication date: 6-Nov-2009
https://dl.acm.org/doi/10.5555/1987717.1987730
Suzuki YFukumoto FChoudhury MHassan SMukherjee AMuresan S(2009)Classifying Japanese polysemous verbs based on fuzzy C-means clusteringProceedings of the 2009 Workshop on Graph-based Methods for Natural Language Processing10.5555/1708124.1708132(32-40)Online publication date: 7-Aug-2009
https://dl.acm.org/doi/10.5555/1708124.1708132
Miyao YTsujii JKoehn PMihalcea R(2009)Supervised learning of a probabilistic lexicon of verb semantic classesProceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 310.5555/1699648.1699679(1328-1337)Online publication date: 6-Aug-2009
https://dl.acm.org/doi/10.5555/1699648.1699679
Sun LKorhonen AKrymolowski Y(2008)Verb class discovery from rich syntactic dataProceedings of the 9th international conference on Computational linguistics and intelligent text processing10.5555/1787578.1787581(16-27)Online publication date: 17-Feb-2008
https://dl.acm.org/doi/10.5555/1787578.1787581
Abend OReichart RRappoport AScott DUszkoreit H(2008)A supervised algorithm for verb disambiguation into VerbNet classesProceedings of the 22nd International Conference on Computational Linguistics - Volume 110.5555/1599081.1599083(9-16)Online publication date: 18-Aug-2008
https://dl.acm.org/doi/10.5555/1599081.1599083
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