paper-with-me

홈 › Papers

LiMe: a Latin Corpus of Late Medieval Criminal Sentences

2024-04-19 · Alessandra Bassani, Beatrice Del Bo, Alfio Ferrara, Marta Mangini, Sergio Picascia, Ambra Stefanello

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.

📄 PDF Abstract BibTeX arXiv:2404.12829

Code (0)

등록된 구현이 없습니다.

Tasks

Language ModelingLanguage Modelling

Methods 이 논문이 사용한 방법론

LIME LIME, or Local Interpretable Model-Agnostic Explanations, is an algorithm that can explain the predictions of any classifier or regressor in a faithful way, by…

Similar Papers 제목 키워드 기반

eFontes. Part of Speech Tagging and Lemmatization of Medieval Latin Texts.A Cross-Genre Survey

2024-06-29 · Krzysztof Nowak, Jędrzej Ziębura, Krzysztof Wróbel, Aleksander Smywiński-Pohl

This study introduces the eFontes models for automatic linguistic annotation of Medieval Latin texts, focusing on lemmatization, part-of-speech tagging, and morphological feature determination. Using the Transformers lib…

Lemmatizationnamed-entity-recognitionNamed Entity RecognitionPart-Of-Speech Tagging

People and Places of Historical Europe: Bootstrapping Annotation Pipeline and a New Corpus of Named Entities in Late Medieval Texts

2023-05-26 · Vít Novotný, Kristýna Luger, Michal Štefánik, Tereza Vrabcová 외

Although pre-trained named entity recognition (NER) models are highly accurate on modern corpora, they underperform on historical texts due to differences in language OCR errors. In this work, we develop a new NER corpus…

Information Retrievalnamed-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)+5

Multilingual Named Entity Recognition for Medieval Charters Using Stacked Embeddings and Bert-based Models.

2022-06-01 · LT4HALA (LREC) 2022 6 · Sergio Torres Aguilar

In recent years the availability of medieval charter texts has increased thanks to advances in OCR and HTR techniques. But the lack of models that automatically structure the textual output continues to hinder the extrac…

HTRMultilingual Named Entity Recognitionnamed-entity-recognitionNamed Entity Recognition+2

Democratizing the medieval English legal tradition

2026-05-01 · Michael Zhang, Elise Wang, Charlotte Whatley, Seth Strickland 외 arxiv

The record of the beginning of the most widespread legal system in the world is contained in millions of pages of handwritten text. Most of the records of the first centuries of the Anglo-American legal system are hand-w…

Handwriting Recognition

Comparative Analysis of Static and Contextual Embeddings for Analyzing Semantic Changes in Medieval Latin Charters

2024-10-11 · Yifan Liu, Gelila Tilahun, Xinxiang Gao, Qianfeng Wen 외

The Norman Conquest of 1066 C.E. brought profound transformations to England's administrative, societal, and linguistic practices. The DEEDS (Documents of Early England Data Set) database offers a unique opportunity to e…

Word Embeddings