Exploring the Syntax-Semantic Interface in Computational Models

• Thesis title in Czech: Výzkum rozhraní syntaxe a sémantiky ve výpočetních modelech
• Thesis title in English: Exploring the Syntax-Semantic Interface in Computational Models
• Key words: universal dependencies|latina|syntaktická analýza|Sémantická reprezentace/Uniform meaning repre.
• English key words: universal dependencies|latin|syntactic parsing|Semantic representation/Uniform meaning repre.
• Academic year of topic announcement: 2021/2022
• Thesis type: dissertation
• Thesis language: angličtina
• Department: Institute of Formal and Applied Linguistics (32-UFAL)
• Supervisor: doc. RNDr. Daniel Zeman, Ph.D.
• Author: hidden - assigned and confirmed by the Study Dept.
• Date of registration: 08.02.2022
• Date of assignment: 08.02.2022
• Confirmed by Study dept. on: 07.03.2022

Guidelines

Understanding how structural patterns in language influence meaning is crucial for accurately
capturing the syntax-semantics interface within computational frameworks. This thesis will
explore the interaction between syntactic structures and semantic representations, aiming to
address key challenges in how meaning is shaped by syntax. Special attention will be paid to
Latin, but the study will be placed in the broader context of other languages. Indeed, Latin has
been pivotal in the development of computational linguistics, particularly among ancient
languages, due to its rich resources and historical importance [1]. Considerable research has
focused on Latin syntax (e.g. [2,3,4]), as reflected by the numerous Latin treebanks in
Universal Dependencies [5], spanning various centuries, regions, and literary genres and
indirectly capturing the language variability that arises from Latin's long history and wide
geographical use [6]. However, the interplay between syntax and semantics has not yet been
fully explored and could benefit from a more comprehensive, crosslingual perspective. By
examining Latin alongside other diverse languages through the lens of both syntactic and
semantic approaches, including frameworks such as Uniform Meaning Representation (UMR)[7], this research will contribute to a more integrated understanding of how syntax and
semantics interact in computational models for various languages.

References

[1] Julianne Nyhan and Marco Passarotti. 2019. Introduction, or Why Busa Still Matters, in
Julianne Nyhan and Marco Passarotti (eds.), One Origin of Digital Humanities. Fr. Roberto
Busa in His Own Words, Springer International Publishing, Cham, Germany, pp. 1-17. ISBN:
978-3-030-18311-0.
[2] Marco Passarotti and Felice Dell’Orletta. 2010. Improvements in parsing the index
Thomisticus treebank. Revision, combination and a feature model for medieval Latin. In
Proceedings of the Seventh International Conference on Language Resources and Evaluation
(LREC’10), Valletta, Malta. European Language Resources Association (ELRA).
[3] Marco Passarotti and Paolo Ruffolo. 2010. Parsing the Index Thomisticus Treebank. Some
Preliminary Results. In 15th International Colloquium on Latin Linguistics, pages 714–725.
Innsbrucker Beiträge zur Sprachwissenschaft.
[4] Edoardo Maria Ponti and Marco Passarotti. 2016. Differentia compositionem facit. a
slower-paced and reliable parser for Latin. In Proceedings of the Tenth International
Conference on Language Resources and Evaluation (LREC’16), pages 683–688, Portorož,
Slovenia. European Language Resources Association (ELRA).
[5] Marie-Catherine de Marneffe, Christopher Manning, Joakim Nivre, and Daniel Zeman.
2021. Universal Dependencies. Computational Linguistics, 47(2):255–308.
[6] Rachele Sprugnoli, Marco Passarotti, Flavio Massimiliano Cecchini, and Matteo
Pellegrini. 2020. Overview of the EvaLatin 2020 Evaluation Campaign. In Proceedings of
LT4HALA 2020 - 1st Workshop on Language Technologies for Historical and Ancient
Languages, pages 105–110, Marseille, France. European Language Resources Association
(ELRA).
[7] Jens Van Gysel, Meagan Vigus, Jayeol Chun, Kenneth Lai, Sarah Moeller, Jiarui Yao,
Timothy J. O’Gorman, Andrew Cowell, W. Bruce Croft, ChuRen Huang, Jan Hajic, James H.
Martin, Stephan Oepen, Martha Palmer, James Pustejovsky, Rosa Vallejos, and Nianwen Xue.
2021. Designing a Uniform Meaning Representation for Natural Language Processing.
Künstliche Intell., 35:343–360.