Multiword Expressions: A Pain in the Neck for NLP
CICLing '02 Proceedings of the Third International Conference on Computational Linguistics and Intelligent Text Processing
Automatic identification of non-compositional phrases
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
An empirical model of multiword expression decomposability
MWE '03 Proceedings of the ACL 2003 workshop on Multiword expressions: analysis, acquisition and treatment - Volume 18
Japanese idiom recognition: drawing a line between literal and idiomatic meanings
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Unsupervised recognition of literal and non-literal use of idiomatic expressions
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Automatic identification of non-compositional multi-word expressions using latent semantic analysis
MWE '06 Proceedings of the Workshop on Multiword Expressions: Identifying and Exploiting Underlying Properties
Distinguishing subtypes of multiword expressions using linguistically-motivated statistical measures
MWE '07 Proceedings of the Workshop on a Broader Perspective on Multiword Expressions
Semantics-based multiword expression extraction
MWE '07 Proceedings of the Workshop on a Broader Perspective on Multiword Expressions
MWE '07 Proceedings of the Workshop on a Broader Perspective on Multiword Expressions
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Handling sparsity for verb noun MWE token classification
GEMS '09 Proceedings of the Workshop on Geometrical Models of Natural Language Semantics
Task-based evaluation of multiword expressions: a pilot study in statistical machine translation
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Hungarian corpus of light verb constructions
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Linguistic cues for distinguishing literal and non-literal usages
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Identification of reduplicated multiword expressions using CRF
CICLing'11 Proceedings of the 12th international conference on Computational linguistics and intelligent text processing - Volume Part I
Identifying verbal collocations in wikipedia articles
TSD'11 Proceedings of the 14th international conference on Text, speech and dialogue
A cascaded classification approach to semantic head recognition
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Unsupervised identification of persian compound verbs
MICAI'11 Proceedings of the 10th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
Combining resources for MWE-token classification
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
Learning to detect english and hungarian light verb constructions
ACM Transactions on Speech and Language Processing (TSLP) - Special issue on multiword expressions: From theory to practice and use, part 1
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We address the problem of classifying multiword expression tokens in running text. We focus our study on Verb-Noun Constructions (VNC) that vary in their idiomaticity depending on context. VNC tokens are classified as either idiomatic or literal. We present a supervised learning approach to the problem. We experiment with different features. Our approach yields the best results to date on MWE classification combining different linguistically motivated features, the overall performance yields an F-measure of 84.58% corresponding to an F-measure of 89.96% for idiomaticity identification and classification and 62.03% for literal identification and classification.