“Voices of the Great War”: A richly annotated corpus of Italian texts on the First World War

A. Lenci, S. Montemagni, F. Boschetti, IRENE DE FELICE, S. Dei Rossi, F. Dell’Orletta, M. Di Giorgio, M. Miliani, L. C. Passaro, A. Puddu, G. Venturi, N. Labanca

Risultato della ricerca: Contributo alla conferenzaContributo in Atti di Convegnopeer review

Abstract

Voci della Grande Guerra (“Voices of the Great War”) is the first large corpus of Italian historical texts dating back to the period of First World War. This corpus differs from other existing resources in several respects. First, from the linguistic point of view it gives account of the wide range of varieties in which Italian was articulated in that period, namely from a diastratic (educated vs. uneducated writers), diaphasic (low/informal vs. high/formal registers) and diatopic (regional varieties, dialects) points of view. From the historical perspective, through a collection of texts belonging to different genres it represents different views on the war and the various styles of narrating war events and experiences. The final corpus is balanced along various dimensions, corresponding to the textual genre, the language variety used, the author type and the typology of conveyed contents. The corpus is annotated with lemmas, part-of-speech, terminology, and named entities. Significant corpus samples representative of the different “voices” have also been enriched with meta-linguistic and syntactic information. The layer of syntactic annotation forms the first nucleus of an Italian historical treebank complying with the Universal Dependencies standard. The paper illustrates the final resource, the methodology and tools used to build it, and the Web Interface for navigating it.
Lingua originaleInglese
Pagine911-918
Numero di pagine8
Stato di pubblicazionePubblicato - 2020
Evento12th Conference on Language Resources and Evaluation (LREC 2020) - Marseille, France
Durata: 1 gen 2020 → …

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???event.eventtypes.event.conference???12th Conference on Language Resources and Evaluation (LREC 2020)
CittàMarseille, France
Periodo1/01/20 → …

Keywords

  • Historical Corpora
  • Information Extraction
  • Linguistic and Meta–linguistic Annotation

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