Papers by Francesco Mambrini

3 papers
Exploring Neural Topic Modeling on a Classical Latin Corpus (2024.lrec-main)

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Challenge: Using topic modeling, it is possible to study Latin literature through methods and tools that support distant reading.
Approach: They propose to use topic modeling to investigate thematic distribution of Latin corpus . they train, optimize and compare two neural models to evaluate which performs better .
Outcome: The proposed model is compared with two neural models with a Classical Latin corpus and shows that it is coherent and interpretable.
Modelling and Linking an Old Latin-Portuguese Dictionary to the LiLa Knowledge Base (2024.lrec-main)

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Challenge: lexical and lexicographic information of Antonio Velez's bilingual Latin-Portuguese dictionary was modelled using the Lexicon Model for Ontologies and its lexicog module.
Approach: This paper describes steps undertaken to include data from Antonio Velez’s bilingual Latin-Portuguese dictionary into the LiLa Knowledge Base of interoperable linguistic resources for Latin.
Outcome: The proposed model includes lexical and lexicographic information from the source dictionary with those of the LiLa collection of Latin lemmas.
The Index Thomisticus Treebank as Linked Data in the LiLa Knowledge Base (2022.lrec-1)

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Challenge: a series of Latin treebanks with word-by-word account of syntax and morphology of Latin texts have been published only in recent years.
Approach: They propose to publish Latin treebanks that contain morphology and syntax annotations . they propose to use principles of the Linguistic Linked Open Data community .
Outcome: The proposed approach enables interoperability between corpora and lexical resources for Latin . language learning and corpus-based research are the most obvious applications .

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