Search Results for author: Flavio Massimiliano Cecchini

Found 8 papers, 1 papers with code

A Treebank-based Approach to the Supprema Constructio in Dante’s Latin Works

1 code implementation LT4HALA (LREC) 2022 Flavio Massimiliano Cecchini, Giulia Pedonese

This paper aims to apply a corpus-driven approach to Dante Alighieri’s Latin works using UDante, a treebank based on Dante Search and part of the Universal Dependencies project.

Sentence

Overview of the EvaLatin 2022 Evaluation Campaign

no code implementations LT4HALA (LREC) 2022 Rachele Sprugnoli, Marco Passarotti, Flavio Massimiliano Cecchini, Margherita Fantoli, Giovanni Moretti

This paper describes the organization and the results of the second edition of EvaLatin, the campaign for the evaluation of Natural Language Processing tools for Latin.

Lemmatization Part-Of-Speech Tagging

Overview of the EvaLatin 2020 Evaluation Campaign

no code implementations LREC 2020 Rachele Sprugnoli, Marco Passarotti, Flavio Massimiliano Cecchini, Matteo Pellegrini

This also allows us to propose the Cross-genre and Cross-time subtasks for each task, in order to evaluate the portability of NLP tools for Latin across different genres and time periods.

Lemmatization Part-Of-Speech Tagging

Challenges in Converting the Index Thomisticus Treebank into Universal Dependencies

no code implementations WS 2018 Flavio Massimiliano Cecchini, Marco Passarotti, Paola Marongiu, Daniel Zeman

The changes are made both to harmonise the Universal Dependencies version of the \textit{Index Thomisticus} Treebank with the two other available Latin treebanks and to fix errors and inconsistencies resulting from the original process.

Dependency Parsing POS +1

Named entity recognition using conditional random fields with non-local relational constraints

no code implementations7 Oct 2013 Flavio Massimiliano Cecchini, Elisabetta Fersini

We begin by introducing the Computer Science branch of Natural Language Processing, then narrowing the attention on its subbranch of Information Extraction and particularly on Named Entity Recognition, discussing briefly its main methodological approaches.

named-entity-recognition Named Entity Recognition +1

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