@inproceedings{bassani-etal-2024-lime,
    title = "{L}i{M}e: A {L}atin Corpus of Late Medieval Criminal Sentences",
    author = "Bassani, Alessanda Clara Carmela  and
      Del Bo, Beatrice Giovanna Maria  and
      Ferrara, Alfio  and
      Mangini, Marta Luigina  and
      Picascia, Sergio  and
      Stefanello, Ambra",
    editor = "Sprugnoli, Rachele  and
      Passarotti, Marco",
    booktitle = "Proceedings of the Third Workshop on Language Technologies for Historical and Ancient Languages (LT4HALA) @ LREC-COLING-2024",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.lt4hala-1.6",
    pages = "41--49",
    abstract = "The Latin language has received attention from the computational linguistics research community, which has built, over the years, several valuable resources, ranging from detailed annotated corpora to sophisticated tools for linguistic analysis. With the recent advent of large language models, researchers have also started developing models capable of generating vector representations of Latin texts. The performances of such models remain behind the ones for modern languages, given the disparity in available data. In this paper, we present the LiMe dataset, a corpus of 325 documents extracted from a series of medieval manuscripts called Libri sententiarum potestatis Mediolani, and thoroughly annotated by experts, in order to be employed for masked language model, as well as supervised natural language processing tasks.",
}

The Latin language has received attention from the computational linguistics research community, which has built, over the years, several valuable resources, ranging from detailed annotated corpora to sophisticated tools for linguistic analysis. With the recent advent of large language models, researchers have also started developing models capable of generating vector representations of Latin texts. The performances of such models remain behind the ones for modern languages, given the disparity in available data. In this paper, we present the LiMe dataset, a corpus of 325 documents extracted from a series of medieval manuscripts called Libri sententiarum potestatis Mediolani, and thoroughly annotated by experts, in order to be employed for masked language model, as well as supervised natural language processing tasks.
Bassani, Aless a Clara Carmela Del Bo, Beatrice Giovanna Maria Ferrara, Alfio Mangini, Marta Luigina Picascia, Sergio Stefanello, Ambra
LiMe: A Latin Corpus of Late Medieval Criminal Sentences