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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 Hits 1 – 20 of 55 1 Semantic Data Set Construction from Human Clustering and Spatial Arrangement ... Majewska, Olga; McCarthy, Diana; Van Den Bosch, Jasper JF. - : Apollo - University of Cambridge Repository, 2021 BASE Show details 2 Context vs Target Word: Quantifying Biases in Lexical Semantic Datasets ... Liu, Qianchu; McCarthy, Diana; Korhonen, Anna. - : arXiv, 2021 BASE Show details 3 AM2iCo: Evaluating Word Meaning in Context across Low-Resource Languages with Adversarial Examples ... Liu, Qianchu; Ponti, Edoardo M.; McCarthy, Diana. - : arXiv, 2021 BASE Show details 4 AM2iCo: Evaluating Word Meaning in Context across Low-Resource Languages with Adversarial Examples ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Korhonen, Anna; Liu, Qianchu. - : Underline Science Inc., 2021 BASE Show details 5 Quantifying lexical usage: vocabulary pertaining to ecosystems and the environment Burgess, Jacquelin; Wild, Kate; McCarthy, Diana. - : Edinburgh University Press, 2021 BASE Show details 6 Manual Clustering and Spatial Arrangement of Verbs for Multilingual Evaluation and Typology Analysis ... Majewska, Olga; Vulic, Ivan; McCarthy, Diana. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 7 Manual Clustering and Spatial Arrangement of Verbs for Multilingual Evaluation and Typology Analysis ... The 28th International Conference on Computational Linguistics 2020; Korhonen, Anna; Majewska, Olga. - : Underline Science Inc., 2020 BASE Show details 8 Manual Clustering and Spatial Arrangement of Verbs for Multilingual Evaluation and Typology Analysis Majewska, Olga; Vulic, Ivan; McCarthy, Diana. - : International Committee on Computational Linguistics, 2020. : https://www.aclweb.org/anthology/2020.coling-main.423, 2020. : Proceedings of the 28th International Conference on Computational Linguistics (COLING 2020), 2020 BASE Show details 9 Investigating the cross-lingual translatability of VerbNet-style classification. ... Majewska, Olga; Vulić, Ivan; McCarthy, Diana. - : Apollo - University of Cambridge Repository, 2018 BASE Show details 10 Investigating the cross-lingual translatability of VerbNet-style classification. Majewska, Olga; Vulić, Ivan; McCarthy, Diana. - : Springer Science and Business Media LLC, 2018. : Lang Resour Eval, 2018 BASE Show details 11 Licensing Complex Prepositions via Lexical Constraints Trawiński, Beata [Verfasser]; Bond, Francis [Herausgeber]; Korhonen, Anna [Herausgeber]. - Mannheim : Institut für Deutsche Sprache, Bibliothek, 2017 DNB Subject Category Language Show details 12 Investigating the cross-lingual translatability of VerbNet-style classification [<Journal>] Majewska, Olga [Verfasser]; Vulić, Ivan [Sonstige]; McCarthy, Diana [Sonstige]. DNB Subject Category Language Show details 13 Word Sense Clustering and Clusterability McCarthy, Diana; Apidianaki, Marianna; Erk, Katrin In: ISSN: 0891-2017 ; EISSN: 1530-9312 ; Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-01838502 ; Computational Linguistics, Massachusetts Institute of Technology Press (MIT Press), 2016, 42, pp.245-275. &#x27E8;10.1162/COLI&#x27E9; (2016) BASE Show details 14 Integrating character representations into Chinese word embedding Chen, Xingyuan; Jin, Peng; McCarthy, Diana Frances. - : Springer International Publishing, 2016 BASE Show details 15 Inferences during reading Ratcliff, Roger; Broek, Paul van den; Cain, Kate. - Cambridge : Cambridge University Press, 2015 BLLDB UB Frankfurt Linguistik Show details 16 Semantic clustering of pivot paraphrases Apidianaki, Marianna; Verzeni, Emilia; McCarthy, Diana In: International Conference on Language Resources and Evaluation ; https://hal.archives-ouvertes.fr/hal-01838559 ; International Conference on Language Resources and Evaluation, Jan 2014, Reykjavik, Iceland (2014) BASE Show details 17 A lexicographic appraisal of an automatic approach for detecting new wordsenses Cook, Paul; Lau, Jey H.; Rundell, Michael... In: Electronic lexicography in the 21st century: thinking outside the paper. Proceedings of the eLex 2013 conference, 17 - 19 October 2013, Tallinn, Estonia (2013), 49-65 IDS OBELEX meta Show details 18 Quantifying lexical usage: vocabulary pertaining to ecosystems and the environment Wild, Kate; Burgess, Jacquelin; Church, Andrew... In: Corpora. - Edinburgh : Univ. Press 8 (2013) 1, 53-79 BLLDB OLC Linguistik Show details 19 Quantifying lexical usage: vocabulary pertaining to ecosystems and the environment Church, Andrew; McCarthy, Diana; Wild, Kate. - : Edinburgh University Press, 2013 BASE Show details 20 Finding Meaning in Context Using Graph Algorithms in Mono- and Cross-lingual Settings Sinha, Ravi Som. - : University of North Texas, 2013 Abstract: Making computers automatically find the appropriate meaning of words in context is an interesting problem that has proven to be one of the most challenging tasks in natural language processing (NLP). Widespread potential applications of a possible solution to the problem could be envisaged in several NLP tasks such as text simplification, language learning, machine translation, query expansion, information retrieval and text summarization. Ambiguity of words has always been a challenge in these applications, and the traditional endeavor to solve the problem of this ambiguity, namely doing word sense disambiguation using resources like WordNet, has been fraught with debate about the feasibility of the granularity that exists in WordNet senses. The recent trend has therefore been to move away from enforcing any given lexical resource upon automated systems from which to pick potential candidate senses,and to instead encourage them to pick and choose their own resources. Given a sentence with a target ambiguous word, an alternative solution consists of picking potential candidate substitutes for the target, filtering the list of the candidates to a much shorter list using various heuristics, and trying to match these system predictions against a human generated gold standard, with a view to ensuring that the meaning of the sentence does not change after the substitutions. This solution has manifested itself in the SemEval 2007 task of lexical substitution and the more recent SemEval 2010 task of cross-lingual lexical substitution (which I helped organize), where given an English context and a target word within that context, the systems are required to provide between one and ten appropriate substitutes (in English) or translations (in Spanish) for the target word. In this dissertation, I present a comprehensive overview of state-of-the-art research and describe new experiments to tackle the tasks of lexical substitution and cross-lingual lexical substitution. In particular I attempt to answer some research questions pertinent to the tasks, mostly focusing on completely unsupervised approaches. I present a new framework for unsupervised lexical substitution using graphs and centrality algorithms. An additional novelty in this approach is the use of directional similarity rather than the traditional, symmetric word similarity. Additionally, the thesis also explores the extension of the monolingual framework into a cross-lingual one, and examines how well this cross-lingual framework can work for the monolingual lexical substitution and cross-lingual lexical substitution tasks. A comprehensive set of comparative investigations are presented amongst supervised and unsupervised methods, several graph based methods, and the use of monolingual and multilingual information. Keyword: cross lingual; disambiguations; Lexical substitution; word sense URL: http://digital.library.unt.edu/ark:/67531/metadc271899/ BASE Hide details Page: 1 2 3

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