ParlaMint II: advancing comparable parliamentary corpora across Europe

Abstract The paper presents the results of the ParlaMint II project, which comprise comparable corpora of parliamentary debates of 29 European countries and autonomous regions, covering at least the period from 2015 to 2022, and containing over 1 billion words. The corpora are uniformly encoded, contain rich metadata about their 24 thousand speakers, and are linguistically annotated up to the level of Universal Dependencies syntax and named entities. The paper focuses on the enhancement made since the ParlaMint I project and presents the compilation of the corpora, including the encoding infrastructure, use of GitHub, the production of individual corpora, the common pipeline for producing their distribution, and use of CLARIN services for dissemination. It then gives a quantitative overview of the produced corpora, followed by the qualitative additions made within the ParlaMint II project, namely metadata localisation, the addition of new metadata, such as the political orientation of political parties, the machine translation of the corpora to English and its tagging with semantic classes, and the production of pilot speech corpora. Finally, outreach activities and further work are discussed.

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Publication Details

Journal
Language Resources and Evaluation
Published
2024-12-27
DOI
https://doi.org/10.1007/s10579-024-09798-w
Citations
10
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
4.52
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ParlaMint II: advancing comparable parliamentary corpora across Europe

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ParlaMint II: advancing comparable parliamentary corpora across Europe

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article en
10 citations

Abstract

Abstract The paper presents the results of the ParlaMint II project, which comprise comparable corpora of parliamentary debates of 29 European countries and autonomous regions, covering at least the period from 2015 to 2022, and containing over 1 billion words. The corpora are uniformly encoded, contain rich metadata about their 24 thousand speakers, and are linguistically annotated up to the level of Universal Dependencies syntax and named entities. The paper focuses on the enhancement made since the ParlaMint I project and presents the compilation of the corpora, including the encoding infrastructure, use of GitHub, the production of individual corpora, the common pipeline for producing their distribution, and use of CLARIN services for dissemination. It then gives a quantitative overview of the produced corpora, followed by the qualitative additions made within the ParlaMint II project, namely metadata localisation, the addition of new metadata, such as the political orientation of political parties, the machine translation of the corpora to English and its tagging with semantic classes, and the production of pilot speech corpora. Finally, outreach activities and further work are discussed.

Language Resources and EvaluationVol. 59(3)
Universitat Jaume I (ES), Uppsala University (SE), University of Copenhagen (DK), Centre National de la Recherche Scientifique (FR), University of Helsinki (FI), Austrian Academy of Sciences (AT), University of Lisbon (PT), University of the Basque Country (ES), Universitat Pompeu Fabra (ES), Universidade de Santiago de Compostela (ES), Université Paul-Valéry Montpellier (FR), Charles University (CZ), Bulgarian Academy of Sciences (BG), ELTE Research Centre for Linguistics (HU), Jožef Stefan Institute (SI), Polish-Japanese Academy of Information Technology (PL), Árni Magnússon Institute for Icelandic Studies (IS), Institute of Computer Science (PL), The National Institute for Strategic Studies (UA), Jožef Stefan International Postgraduate School (SI), Austrian Centre for Digital Humanities (AT), National Archives Services of Norway (NO), Institute for Computational Linguistics “A. Zampolli” (IT), Institute of Contemporary History (SI), Athena Research and Innovation Center In Information Communication & Knowledge Technologies (GR), Institute of Information and Communication Technologies (BG), University of Tartu (EE), Lancaster University (GB), University of Tübingen (DE), University of Amsterdam (NL), University of Latvia (LV), Polish Academy of Sciences (PL)
Industry, innovation and infrastructure
Openalex Percentile: Top 5%
Natural Language Processing Techniques
4.52
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