Despite the headway made in the last decade in building, sharing and exploiting linguistic resources and tools for the automatic processing of Latin, these remain incompatible.
The objective of LiLa (2018-2023) is to connect and ultimately exploit the wealth of linguistic resources and NLP tools for Latin created so far, in order to bridge the gap between raw language data, NLP and knowledge descriptions. To do so, LiLa is building an open-ended Knowledge Base using the Linked Data paradigm, concurrently adding Latin to the multilingual Linguistic Linked Open Data (LLOD) cloud.Read more →
Software developer, expert in NLP, data analysis and visualisation.
MA Student in Theoretical and Applied Linguistics. Collaborates on modelling tagsets for Latin PoS-tagging using ontologies.
Modern philology and semantics graduate. Collaborates on the evaluation and extension of the Latin WordNet.
Foreign Languages graduate. Collaborates on sentiment analysis for Latin.
Visiting Scholar from UniHelsinki, author of the Late Latin Charter Treebank (LLCT).