In this paper we describe some experiments related to a corpus derived from an authoritative historical Italian dictionary, namely the Grande dizionario della lingua italiana (‘Great Dictionary of Italian Language’, in short GDLI). Thanks to the digitization and structuring of this dictionary, we have been able to set up the first nucleus of a diachronic annotated corpus that selects—according to specific criteria, and distinguishing between prose and poetry—some of the quotations that within the entries illustrate the different definitions and sub-definitions. In fact, the GDLI presents a huge collection of quotations covering the entire history of the Italian language and thus ranging from the Middle Ages to the present day. The corpus was enriched with linguistic annotation and used to train and evaluate NLP models for POS tagging and lemmatization, with promising results.
Towards the Creation of a Diachronic Corpus for Italian: A Case Study on the GDLI Quotations / Favaro, Manuel; Guadagnini, Elisa; Sassolini, Eva; Biffi, Marco; Montemagni, Simonetta. - (2022), pp. 94-100. (Intervento presentato al convegno LREC 2022 tenutosi a Marsiglia).
Towards the Creation of a Diachronic Corpus for Italian: A Case Study on the GDLI Quotations
Manuel FavaroPrimo
Writing – Original Draft Preparation
;Elisa GuadagniniWriting – Original Draft Preparation
;
2022
Abstract
In this paper we describe some experiments related to a corpus derived from an authoritative historical Italian dictionary, namely the Grande dizionario della lingua italiana (‘Great Dictionary of Italian Language’, in short GDLI). Thanks to the digitization and structuring of this dictionary, we have been able to set up the first nucleus of a diachronic annotated corpus that selects—according to specific criteria, and distinguishing between prose and poetry—some of the quotations that within the entries illustrate the different definitions and sub-definitions. In fact, the GDLI presents a huge collection of quotations covering the entire history of the Italian language and thus ranging from the Middle Ages to the present day. The corpus was enriched with linguistic annotation and used to train and evaluate NLP models for POS tagging and lemmatization, with promising results.File | Dimensione | Formato | |
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