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1
Multi-unit association measures: Moving beyond pairs of words
Dunn J. - 2019
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2
What Metaphor Identification Systems Can Tell Us About Metaphor-in-Language
Dunn J. - 2019
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3
Frequency vs. Association for Constraint Selection in Usage-Based Construction Grammar
Dunn J. - : Association for Computational Linguistics, 2019
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4
Measuring Metaphoricity
Dunn J. - 2019
Abstract: This paper presents the first computationally-derived scalar measurement of metaphoricity. Each input sentence is given a value between 0 and 1 which represents how metaphoric that sentence is. This measure achieves a correlation of 0.450 (Pearson’s R, p <0.01) with an experimental measure of metaphoricity involving human participants. While far from perfect, this scalar measure of metaphoricity allows different thresholds for metaphoricity so that metaphor identification can be fitted for specific tasks and datasets. When reduced to a binary classification evaluation using the VU Amsterdam Metaphor Corpus, the system achieves an F-Measure of 0.608, slightly lower than the comparable binary classification system’s 0.638 and competitive with existing approaches.
Keyword: Communication and Culture::2004 - Linguistics::200402 - Computational Linguistics; communication and culture::4704 - Linguistics::470409 - Linguistic structures (incl. phonology; Field of Research::17 - Psychology and Cognitive Sciences::1702 - Cognitive Science::170204 - Linguistic Processes (incl. Speech Production and Comprehension); Field of Research::20 - Language; Fields of Research::47 - Language; morphology and syntax)
URL: http://hdl.handle.net/10092/17136
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5
Multi-Dimensional Abstractness in Cross-Domain Mappings
Dunn J. - 2019
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6
Modeling the Complexity and Descriptive Adequacy of Construction Grammars
Dunn J. - 2019
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7
Global Syntactic Variation in Seven Languages: Towards a Computational Dialectology
Dunn J. - 2019
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8
Language-Independent Ensemble Approaches to Metaphor Identification
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9
How linguistic structure influences and helps to predict metaphoric meaning
Dunn J. - : Walter de Gruyter GmbH, 2019
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