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Language access and content enrichment of Brepols' full-text databases: an AI and NLP-based transformation into a dynamic research, reading and learning environment

Based on the most recent developments in computational linguistics, Artificial Intelligence and Natural Language Processing (NLP), this Baekeland mandate strives for a multi-layered connection, deepening and enrichment of Brepols' Latin and Greek text corpus, both from a linguistic and content-based perspective, each time on word, sentence and text level. This transformed and enriched corpus will form the backbone of a dynamic research, reading and learning environment, optimally embedded in the online Brepolis platform, in the form of (1) ready-to-use tools for standard users, (2) an encrypted interface for specialized research teams, and, in the longer term, (3) a digital learning environment for school and undergraduate students. From a scientific point of view, this project investigates how robust NLP methods can be used for limited historical, inflectional corpus languages, of which the added value of domain knowledge is explicitly studied.

Date:1 Oct 2021 →  Today
Keywords:NLP, AI, Latin, Ancient Greek, Transformers, Digital Humanities, Corpus Linguistics, Full-text Databases
Disciplines:Computational linguistics
Project type:PhD project