A multi-sense context-agnostic definition generation model evaluated on multiple languages

dc.contributor.advisorCook, Paul
dc.contributor.authorKabiri, Arman
dc.date.accessioned2023-03-01T16:23:39Z
dc.date.available2023-03-01T16:23:39Z
dc.date.issued2020
dc.date.updated2023-03-01T15:02:02Z
dc.description.abstractDefinition modeling is a recently-introduced task in natural language processing (NLP) which aims to predict and generate dictionary-style definitions for any given word. Most prior work on definition modelling has not accounted for polysemy — i.e. a linguistic phenomenon in which a word can imply multiple meanings when used in various contexts — or has done so by considering definition modelling for a target word in a given context. In contrast, in this study, we propose a context-agnostic approach to definition modelling, based on multi-sense word embeddings, that is capable of generating multiple definitions for a target word. In further contrast to most prior work, which has primarily focused on English, we evaluate our proposed approach on fifteen different datasets covering nine languages from several language families. To evaluate our approach we consider several variations of BLEU — i.e., a widely-used evaluation metric initially introduced for machine translation that is adapted to definition modeling. Our results demonstrate that our proposed multisense model outperforms a single-sense model on all fifteen datasets.
dc.description.copyright© Arman Kabiri, 2020
dc.formattext/xml
dc.format.extentix, 87 pages
dc.format.mediumelectronic
dc.identifier.urihttps://unbscholar.lib.unb.ca/handle/1882/13726
dc.language.isoen_CA
dc.publisherUniversity of New Brunswick
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subject.disciplineComputer Science
dc.titleA multi-sense context-agnostic definition generation model evaluated on multiple languages
dc.typemaster thesis
thesis.degree.disciplineComputer Science
thesis.degree.fullnameMaster of Computer Science
thesis.degree.grantorUniversity of New Brunswick
thesis.degree.levelmasters
thesis.degree.nameM.C.S.

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