This paper focuses on the challenges of creating a structured digital database from large datasets that were not originally digital and lack a rigorous organizational structure. A representative case is the computerization of Salvatore Battaglia's Grande Dizionario della Lingua Italiana (GDLI). This initiative part of a broader effort to recover, preserve, and enhance textual resources of historical, linguistic, and cultural significance. Due to its monumental nature, the original print format of the GDLI is highly complex. Although Optical Character Recognition (OCR) technology enables digitization, it is not immune to orthographic errors. The project, born as a collaboration between the Accademia della Crusca and the A. Zampolli Institute for Computational Linguistics (CNR-ILC), involves the creation of an online searchable database with advanced search capabilities. Currently digital dictionaries are widely available accessible on the Internet, attracting a diverse range of users. The GDLI, in particular, has been extensively consulted since becoming available online in its unstructured form. The project seeks to provide structured access tailored to the needs of linguists and language historians. The chosen work solutions and implementation strategies stem from a thorough analysis of the data and the potential uses of the dictionary’s information. The approach balances error management with the creation of a hybrid data representation model-one that is not a traditional database but rather a network of interconnected yet autonomous resources. The result is a multidimensional database capable of supporting diverse perspectives for analysis and consultation.

Exploring the GDLI: a multidimensional approach to Historical Lexicography / Marco Biffi, S.C.. - ELETTRONICO. - (2025), pp. 483-487. (2025 IEEE 8th Congress on Information Science and Technology (CiSt) Marrakech, Marocco 4-10 ottobre 2025) [10.1109/CiSt65886.2025.11224195].

Exploring the GDLI: a multidimensional approach to Historical Lexicography

Marco Biffi
;
Sebastiana Cucurullo;Eva Sassolini
2025

Abstract

This paper focuses on the challenges of creating a structured digital database from large datasets that were not originally digital and lack a rigorous organizational structure. A representative case is the computerization of Salvatore Battaglia's Grande Dizionario della Lingua Italiana (GDLI). This initiative part of a broader effort to recover, preserve, and enhance textual resources of historical, linguistic, and cultural significance. Due to its monumental nature, the original print format of the GDLI is highly complex. Although Optical Character Recognition (OCR) technology enables digitization, it is not immune to orthographic errors. The project, born as a collaboration between the Accademia della Crusca and the A. Zampolli Institute for Computational Linguistics (CNR-ILC), involves the creation of an online searchable database with advanced search capabilities. Currently digital dictionaries are widely available accessible on the Internet, attracting a diverse range of users. The GDLI, in particular, has been extensively consulted since becoming available online in its unstructured form. The project seeks to provide structured access tailored to the needs of linguists and language historians. The chosen work solutions and implementation strategies stem from a thorough analysis of the data and the potential uses of the dictionary’s information. The approach balances error management with the creation of a hybrid data representation model-one that is not a traditional database but rather a network of interconnected yet autonomous resources. The result is a multidimensional database capable of supporting diverse perspectives for analysis and consultation.
2025
2025 IEEE 8th Congress on Information Science and Technology (CiSt)
2025 IEEE 8th Congress on Information Science and Technology (CiSt)
Marrakech, Marocco
4-10 ottobre 2025
Marco Biffi, Sebastiana Cucurullo, Eva Sassolini
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1499102
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