This paper describes the first edition of EvaLatin, a campaign totally devoted to the evaluation of NLP tools for Latin. The two shared tasks proposed in EvaLatin 2020, i. e. Lemmatization and Part-of-Speech tagging, are aimed at fostering research in the field of language technologies for Classical languages. The shared dataset consists of texts taken from the Perseus Digital Library, processed with UDPipe models and then manually corrected by Latin experts. The training set includes only prose texts by Classical authors. The test set, alongside with prose texts by the same authors represented in the training set, also includes data relative to poetry and to the Medieval period. 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. The results obtained by the participants for each task and subtask are presented and discussed.
Sprugnoli, R., Passarotti, M. C., Cecchini, F. M., Pellegrini, M., Overview of the EvaLatin 2020 Evaluation Campaign, in Proceedings of LT4HALA 2020 Workshop - 1st Workshop on Language Technologies for Historical and Ancient Languages, satellite event to the Twelfth International Conference on Language Resources and Evaluation (LREC 2020), (Marsiglia, 12-12 May 2020), European Language Resources Association (ELRA), Paris 2020: 105-110 [http://hdl.handle.net/10807/151970]
Overview of the EvaLatin 2020 Evaluation Campaign
Sprugnoli, Rachele;Passarotti, Marco Carlo;Cecchini, Flavio Massimiliano;Pellegrini, Matteo
2020
Abstract
This paper describes the first edition of EvaLatin, a campaign totally devoted to the evaluation of NLP tools for Latin. The two shared tasks proposed in EvaLatin 2020, i. e. Lemmatization and Part-of-Speech tagging, are aimed at fostering research in the field of language technologies for Classical languages. The shared dataset consists of texts taken from the Perseus Digital Library, processed with UDPipe models and then manually corrected by Latin experts. The training set includes only prose texts by Classical authors. The test set, alongside with prose texts by the same authors represented in the training set, also includes data relative to poetry and to the Medieval period. 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. The results obtained by the participants for each task and subtask are presented and discussed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.