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Výpočetní modely konkurence v přirozených jazycích
Thesis title in Czech: Výpočetní modely konkurence v přirozených jazycích
Thesis title in English: Computational Models of Competition in Natural Languages
Key words: synonymy|language means competition
Academic year of topic announcement: 2023/2024
Type of assignment: dissertation
Thesis language:
Department: Institute of Formal and Applied Linguistics (32-UFAL)
Supervisor: doc. Ing. Zdeněk Žabokrtský, Ph.D.
Author: hidden - assigned and confirmed by the Study Dept.
Date of registration: 15.09.2023
Date of assignment: 15.09.2023
Confirmed by Study dept. on: 26.09.2023
In natural languages, a semantically relevant category can often be expressed by more than one form. We can observe a competition on various levels on linguistic abstraction, such as a competition among inflectional paradigms, among derivational affixes, or among syntactic constructions ([1]). Such synonymous patterns (in a broad sense) sometimes belong to different levels, for example, in the case of a rivalry between a word-formation means and an inflectional means that can be both used for expressing the same meaning. The goal of the thesis is to develop computational models for capturing such phenomena cross-linguistically, using evidence from modern multilingual corpora ([2],[3]) and other multilingual language data resources ([4],[5]).

[1] Rainer, Franz, et al., eds. Competition in Inflection and Word-formation. Springer International Publishing, 2019.

[2] Christodouloupoulos, Christos, and Mark Steedman. "A massively parallel corpus: the Bible in 100 languages." Language resources and evaluation 49.2 (2015): 375-395.

[3] Nivre, Joakim, et al. "Universal dependencies v1: A multilingual treebank collection." Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16). 2016.

[4] Kyjánek, Lukáš, et al. "Universal Derivations Kickoff: A Collection of Harmonized Derivational Resources for Eleven Languages." Proceedings of the Second International Workshop on Resources and Tools for Derivational Morphology. 2019.

[5] Batsuren, Khuyagbaatar, Gabor Bella, and Fausto Giunchiglia. "CogNet: A Large-Scale Cognate Database." Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. 2019.
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