An empirical model of multiword expression decomposability

Baldwin, Timothy; Bannard, Colin; Tanaka, Takaaki; Widdows, Dominic

doi:10.3115/1119282.1119294

Cited by 142 publications

(102 citation statements)

References 15 publications

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“…Previous studies determine compositionality by looking at the degree of distributional similarity between an expression and its component words (e.g., McCarthy et al, 2003;Bannard et al, 2003;Baldwin et al, 2003). Because light verbs are highly polysemous and frequently used in LVCs, such an approach is not appropriate for determining their contribution to the semantics of an expression.…”

Section: Discussion and Concluding Remarksmentioning

confidence: 99%

Automatically distinguishing literal and figurative usages of highly polysemous verbs

Fazly

North

Stevenson

2005

Proceedings of the ACL-SIGLEX Workshop on Deep Lexical Acquisition - DeepLA '05

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We investigate the meaning extensions of very frequent and highly polysemous verbs, both in terms of their compositional contribution to a light verb construction (LVC), and the patterns of acceptability of the resulting LVC. We develop compositionality and acceptability measures that draw on linguistic properties specific to LVCs, and demonstrate that these statistical, corpus-based measures correlate well with human judgments of each property.

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Section: Discussion and Concluding Remarksmentioning

confidence: 99%

Automatically distinguishing literal and figurative usages of highly polysemous verbs

Fazly

North

Stevenson

2005

Proceedings of the ACL-SIGLEX Workshop on Deep Lexical Acquisition - DeepLA '05

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“…In many later works distributional models were used. Baldwin et al (2003) showed that LSA-based similarity between the multiword expression and each of its components is indicative for compositionality. Katz and Giesbrecht (2006) compared the actual phrase vector to the estimated compositional meaning vector calculated as a sum of the meaning vectors of the 772 parts.…”

Section: Existing Workmentioning

confidence: 99%

Detecting Metaphorical Phrases in the Polish Language

Wawer

Mykowiecka

2017

RANLP 2017 - Recent Advances in Natural Language Processing Meet Deep Learning

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In this paper we describe experiments with automated detection of metaphors in the Polish language. We focus our analysis on noun phrases composed of an adjective and a noun, and distinguish three types of expressions: with literal sense, with metaphorical sense, and expressions both literal and methaphorical (context-dependent). We propose a method of automatically recognizing expression type using word embeddings and neural networks. We evaluate multiple neural network architectures and demonstrate that the method significantly outperforms strong baselines.

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“…Several researchers have used latent semantic analysis (LSA) to distinguish between compositional and non-compositional preferences of expressions [17,18]. They show that compositional MWEs are generally more likely similar to their constituents than other non-compositional MWEs.…”

Section: Mwe Identificationmentioning

confidence: 99%

Bilingual Multiword Expression Alignment by Constituent-Based Similarity Score

Seo¹,

Kwon²,

Cheon³

et al. 2016

J Inf Process Syst

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This paper presents the constituent-based approach for aligning bilingual multiword expressions, such as noun phrases, by considering the relationship not only between source expressions and their target translation equivalents but also between the expressions and constituents of the target equivalents. We only considered the compositional preferences of multiword expressions and not their idiomatic usages because our multiword identification method focuses on their collocational or compositional preferences. In our experimental results, the constituent-based approach showed much better performances than the general method for extracting bilingual multiword expressions. For our future work, we will examine the scoring method of the constituent-based approach in regards to having the best performance. Moreover, we will extend target entries in the evaluation dictionaries by considering their synonyms.

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An empirical model of multiword expression decomposability

Cited by 142 publications

References 15 publications

Automatically distinguishing literal and figurative usages of highly polysemous verbs

Automatically distinguishing literal and figurative usages of highly polysemous verbs

Detecting Metaphorical Phrases in the Polish Language

Bilingual Multiword Expression Alignment by Constituent-Based Similarity Score

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