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.
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.
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.
no code implementations • LREC 2020 • Flavio Massimiliano Cecchini, Timo Korkiakangas, Marco Passarotti
The present work introduces a new Latin treebank that follows the Universal Dependencies (UD) annotation standard.
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.
no code implementations • 7 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.