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dc.contributor.advisorAhmad, Khurshid
dc.contributor.authorGerow, Aaron
dc.date.accessioned2016-11-07T14:19:58Z
dc.date.available2016-11-07T14:19:58Z
dc.date.issued2014
dc.identifier.citationAaron Gerow, 'Identification and interpretation of figurative language with computational semantic models', [thesis], Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2014, pp 240
dc.identifier.otherTHESIS 10776
dc.identifier.urihttp://hdl.handle.net/2262/77617
dc.description.abstractThis thesis is about the automatic extraction of metaphors as they appear in English text. This task is important to research in information retrieval, corpus linguistics and computational linguistics. The work was motivated by theories of metaphor comprehension and statistical semantics and contributes to areas of natural language processing (NLP) and information extraction where figurative language continues to present a challenge. Chapter 2 reviews related psychological and computational work and provides a foundation for a method described in chapter 3. Chapter 4 describes my implementation of this method – a system called MetID. Chapter 5 evaluates MetID on three increasingly difficult tasks: identification, interpretation and extraction of figurative language. The final chapter describes the contribution of this research, contextualising it in light of the research goals and concludes with a discussion of future work. Methods and techniques of the project were inspired by research on how people comprehend metaphors, by linguistic research in how metaphor is used in text, and by NLP techniques for extracting particular types of metaphor. The goal was to build and test a system for automatically finding and providing interpretations of figurative language. A central task is representing word associations that account for the semantics of figurative language. Specifically, three types of lexical models were evaluated: WordNet, distributional semantic models and co-occurrence likelihood estimation. The method also uses a number of heuristics that typically mark linguistic metaphor, such as selectional violation and predication. The system can be used to analyse individual phrases, a corpus (which can simultaneously be used to build the lexical model) or a collection using pre-built models. The output is a ranked list of candidate metaphors by which to interpret a statement. For example, analysing “my heart is on fire” produces the interpretation AFFECTION AS WARMTH. The system attempts to account for two common forms: noun- and verb-based metaphors. Evaluation results suggest that the method performs significantly above chance on noun-based statements but not for verb-based. The choice of lexical model has a significant effect when analysing noun-based statements, but not verbs. The results on an interpretation task, which were validated with participant ratings, found that 1) noun-based statements were more easily interpreted, 2) the system was better at interpreting figurative statements than literal statements and 3) in some configurations, the system’s scores correlate strongly to participant ratings. Additionally, an interesting interaction was found: the literal / non-literal distinction mediated the role of a statement’s grammatical form when considering the quality of interpretation. Last, a case study was used to aid a corpus-based terminological analysis of the word contagion in finance and economics where it has been adopted with a number of figurative features.
dc.format1 volume
dc.language.isoen
dc.publisherTrinity College (Dublin, Ireland). School of Computer Science & Statistics
dc.relation.isversionofhttp://stella.catalogue.tcd.ie/iii/encore/record/C__Rb16204243
dc.subjectComputer Science, Ph.D.
dc.subjectPh.D. Trinity College Dublin
dc.titleIdentification and interpretation of figurative language with computational semantic models
dc.typethesis
dc.type.supercollectionrefereed_publications
dc.type.supercollectionthesis_dissertations
dc.type.qualificationlevelDoctoral
dc.type.qualificationnameDoctor of Philosophy (Ph.D.)
dc.rights.ecaccessrightsopenAccess
dc.format.extentpaginationpp 240
dc.description.noteTARA (Trinity's Access to Research Archive) has a robust takedown policy. Please contact us if you have any concerns: rssadmin@tcd.ie


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