Historical Texts into Structured Knowledge Graphs : Introducing Computer-Assisted Semantic Text Modelling in InkVisitor

ZBÍRAL, David, Robert Laurence John SHAW, Tomáš HAMPEJS a Adam MERTEL. Historical Texts into Structured Knowledge Graphs : Introducing Computer-Assisted Semantic Text Modelling in InkVisitor. In Social Networks in Medieval and Renaissance Studies: Thirty Years after Robust Action, Vienna, 21-23 June 2023. 2023.

Základní 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
• Autoři: ZBÍRAL, David, Robert Laurence John SHAW, Tomáš HAMPEJS a Adam MERTEL.
• 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

Anotace

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.

Anotace 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: Název: Networks of Dissent: Computational Modelling of Dissident and Inquisitorial Cultures in Medieval Europe (Akronym: DISSINET)

Investor: Evropská unie, Networks of Dissent: Computational Modelling of Dissident and Inquisitorial Cultures in Medieval Europe, ERC (Excellent Science)