Computational lexicography for natural language
Computational lexicography for natural language
Similarity-Based Models of Word Cooccurrence Probabilities
Machine Learning - Special issue on natural language learning
A vector space model for automatic indexing
Communications of the ACM
Explorations in Automatic Thesaurus Discovery
Explorations in Automatic Thesaurus Discovery
Automatic labeling of semantic roles
Computational Linguistics
Accurate methods for the statistics of surprise and coincidence
Computational Linguistics - Special issue on using large corpora: I
Structural ambiguity and lexical relations
Computational Linguistics - Special issue on using large corpora: I
Using semantic preferences to identify verbal participation in role switching alternations
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Three generative, lexicalised models for statistical parsing
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Automatic retrieval and clustering of similar words
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Principle-based parsing without overgeneration
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Distributional clustering of English words
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Noun classification from predicate-argument structures
ACL '90 Proceedings of the 28th annual meeting on Association for Computational Linguistics
Explaining away ambiguity: learning verb selectional preference with Bayesian networks
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Acquisition of selectional patterns
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Measures of distributional similarity
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Inducing a semantically annotated lexicon via EM-based clustering
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Evaluating and combining approaches to selectional preference acquisition
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 1
Class-based probability estimation using a semantic hierarchy
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
HLT '93 Proceedings of the workshop on Human Language Technology
Disambiguating Nouns, Verbs, and Adjectives Using Automatically Acquired Selectional Preferences
Computational Linguistics
Memory-Based Language Processing (Studies in Natural Language Processing)
Memory-Based Language Processing (Studies in Natural Language Processing)
A distributional model of semantic context effects in lexical processing
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Finding predominant word senses in untagged text
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Discovering asymmetric entailment relations between verbs using selectional preferences
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Dependency-Based Construction of Semantic Space Models
Computational Linguistics
Novel semantic features for verb sense disambiguation
HLT-Short '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers
A robust and extensible exemplar-based model of thematic fit
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Discriminative learning of selectional preference from unlabeled text
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
A structured vector space model for word meaning in context
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Generalizing over lexical features: selectional preferences for semantic role classification
ACLShort '09 Proceedings of the ACL-IJCNLP 2009 Conference Short Papers
Composing and updating verb argument expectations: a distributional semantic model
CMCL '11 Proceedings of the 2nd Workshop on Cognitive Modeling and Computational Linguistics
Semantic relations in bilingual lexicons
ACM Transactions on Speech and Language Processing (TSLP)
Inferring selectional preferences from part-of-speech N-grams
EACL '12 Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
Learning semantics and selectional preference of adjective-noun pairs
SemEval '12 Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation
Regular polysemy: a distributional model
SemEval '12 Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation
Modelling selectional preferences in a lexical hierarchy
SemEval '12 Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation
Investigating the semantics of frame elements
EKAW'12 Proceedings of the 18th international conference on Knowledge Engineering and Knowledge Management
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We present a vector space-based model for selectional preferences that predicts plausibility scores for argument headwords. It does not require any lexical resources (such as WordNet). It can be trained either on one corpus with syntactic annotation, or on a combination of a small semantically annotated primary corpus and a large, syntactically analyzed generalization corpus. Our model is able to predict inverse selectional preferences, that is, plausibility scores for predicates given argument heads. We evaluate our model on one NLP task (pseudo-disambiguation) and one cognitive task (prediction of human plausibility judgments), gauging the influence of different parameters and comparing our model against other model classes. We obtain consistent benefits from using the disambiguation and semantic role information provided by a semantically tagged primary corpus. As for parameters, we identify settings that yield good performance across a range of experimental conditions. However, frequency remains a major influence of prediction quality, and we also identify more robust parameter settings suitable for applications with many infrequent items.