LiMe: a Latin Corpus of Late Medieval Criminal Sentences

TL;DR

This paper introduces LiMe, a thoroughly annotated Latin corpus from late medieval criminal sentences, designed to support the development of language models and NLP tools for Latin, a language with limited digital resources.

Contribution

The paper presents LiMe, a new expert-annotated Latin corpus from medieval manuscripts, enabling improved language modeling and NLP applications for Latin.

Findings

LiMe contains 325 annotated medieval Latin documents.

The corpus supports masked language modeling and supervised NLP tasks.

It aims to bridge the data gap for Latin language models.

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.