A Diachronic Italian Corpus based on L'Unità
Authors: Pierpaolo Basile, Annalina Caputo, Tommaso Caselli, Pierluigi Cassotti, Rossella Varvara (Università di Bari Aldo Moro, Dublin City University, University of Groningen, Università di Firenze, 2020)
Topic: Lexical and Semantic Resources and Analysis

Abstract
In this paper, we describe the creation of a diachronic corpus for Italian by exploiting the digital archive of the newspaper `L'Unità'. We automatically clean and annotate the corpus with PoS tags, lemmas, named entities and syntactic dependencies. Moreover, we compute frequency-based time series for tokens, lemmas and entities. We show some interesting corpus statistics taking into account the temporal dimension and describe some examples of usage of time series.

Introduction
Diachronic linguistics is one of the two major temporal dimensions of language study proposed by de Saussure in his Cours de languistique générale and has a long tradition in Linguistics. Recently, the increasing availability of diachronic corpora as well as the development of new NLP techniques for representing word meanings has boosted the application of computational models to investigate historical language data (Hamilton et al., 2016; Tahmasebi et al., 2018; Tang, 2018). This culminated in SemEval-2020 Unsupervised Lexical Semantic Change Detection (Schlechtweg et al., 2020), the first attempt to systematically evaluate automatic methods for language change detection. Italian is a Romance language which has undergone lots of changes in its history. Its official adoption as a national language occurred only after the Unification of Italy (1861), having previously been a literary language. Diachronic corpora of Italian are currently available and accessible to the public (e.g., DiaCORIS and MIDIA). Unfortunately, restricted access/distribution of these resources limits their utilisation. This actually prevents the investigation of more recent NLP methods to the diachronic dimensions. To obviate this limit, we collect and make freely available a new corpus based on the newspaper “L’Unità”. Founded by Antonio Gramsci on February, 12th 1924, “L’Unità” was the official newspaper of the Italian Communist Party (PCI, henceforth). The newspaper had a troubled history: with the dissolution of PCI in 1991, the newspaper continued to live as the official newspaper of the new Democratic Party of the Left (PDS/DS) until July, 31th 2014. After that date, it ceased its publication until June, 30th 2015, and it was definitely closed on June, 3rd 2017. Since 2017, the historical archive of “L’Unità” has been made again visible and available on the Web. One of the main issues of this resource is the lack of information about who owns the rights of the original archive. To our knowledge, the online version of the archive was legally obtained by downloading the original archive before the closure of the newspaper. The current archive, available online, does not contain the local editions of the newspaper and the photographic archive. The main contribution of this work lies in the resource itself and its accessibility to the research community at large. The corpus is distributed in two formats: raw text and pre-processed. The validity of the corpus for the automatic study of language change is currently tested as part of the DIACR-Ita task at EVALITA 2020. However, we illustrate some further potential applications of the use of the corpus.

Conclusion
In this paper, we describe an Italian diachronic corpus based on the newspaper “L’Unità”. The corpus spans 67 years (1948-2014) and is provided both in plain text and in an annotated format that includes PoS-tags, lemmas, named entities, and syntactic dependencies. We compute some statistics and time series for each token, lemma and named entity. We think that the corpus and the precomputed data are a valuable source of information both for linguists and researchers interested in diachronic analysis of the Italian language, and for historians, political scientists, and journalists as a digital resource enriched with automatic text analysis technologies. However, the corpus has some issues that we plan to fix in the future, such as OCR errors and logical document structure recognition. We also plan to process the corpus by exploiting other Italian NLP pipelines in order to understand the differences between the output of different tools. Finally, we are working on generating and making available temporal word embeddings for each year.