2023
Historical Texts into Structured Knowledge Graphs : Introducing Computer-Assisted Semantic Text Modelling in InkVisitor
ZBÍRAL, David, Robert Laurence John SHAW, Tomáš HAMPEJS a Adam MERTELZákladní údaje
Originální název
Historical Texts into Structured Knowledge Graphs : Introducing Computer-Assisted Semantic Text Modelling in InkVisitor
Název anglicky
Historical Texts into Structured Knowledge Graphs : Introducing Computer-Assisted Semantic Text Modelling in InkVisitor
Vydání
Social Networks in Medieval and Renaissance Studies: Thirty Years after Robust Action, Vienna, 21-23 June 2023, 2023
Další údaje
Typ výsledku
Prezentace na konferencích
Utajení
není předmětem státního či obchodního tajemství
Klíčová slova česky
sémantické modelování textu; digital humanities; náboženský disent
Klíčová slova anglicky
semantic text modelling; digital humanities; inquisition; religious dissidence
Příznaky
Mezinárodní význam, Recenzováno
Změněno: 15. 12. 2023 10:09, Mgr. Jolana Navrátilová
V originále
The paper outlines the methods employed in the DISSINET project for generating structured knowledge graphs from historical data, shedding light on the challenges faced by historians and researchers. The authors introduce Computer-Assisted Semantic Text Modelling (a human-controlled, computer-assisted, statement-based approach to data collection from texts) that seamlessly integrates close reading with computational modeling and transforms texts into rich syntactic-semantic data. The web-based open-source InkVisitor application, which enables creating and linking entities, supports furhter comprehensive analysis. Using the Bologna and Niort trials as illustrative examples, the authors showcase how this approach unveils and elucidates social, spatial, and discursive patterns within medieval dissidence, inquisition trials, and related records. Additionally, the paper delves into the future prospects of machine-produced CASTEMO, leveraging manually collected data as training data for enhanced outcomes.
Anglicky
The paper outlines the methods employed in the DISSINET project for generating structured knowledge graphs from historical data, shedding light on the challenges faced by historians and researchers. The authors introduce Computer-Assisted Semantic Text Modelling (a human-controlled, computer-assisted, statement-based approach to data collection from texts) that seamlessly integrates close reading with computational modeling and transforms texts into rich syntactic-semantic data. The web-based open-source InkVisitor application, which enables creating and linking entities, supports furhter comprehensive analysis. Using the Bologna and Niort trials as illustrative examples, the authors showcase how this approach unveils and elucidates social, spatial, and discursive patterns within medieval dissidence, inquisition trials, and related records. Additionally, the paper delves into the future prospects of machine-produced CASTEMO, leveraging manually collected data as training data for enhanced outcomes.
Návaznosti
101000442, interní kód MU |
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