Publikation:

QT30 : A Corpus of Argument and Conflict in Broadcast Debate

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Datum

2022

Autor:innen

Kikteva, Zlata
Gorska, Kamila
Becker, Ray
Reed, Chris

Herausgeber:innen

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Electronic ISSN

ISBN

Bibliografische Daten

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URI (zitierfähiger Link)
http://nbn-resolving.de/urn:nbn:de:bsz:352-2-10bowcc3rlycy3
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Urheberrechtlich geschützt

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Open Access-Veröffentlichung
Open Access Bookpart

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Linguistik: Publikationen
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Titel in einer weiteren Sprache

Publikationstyp
Beitrag zu einem Konferenzband
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Published

Erschienen in

CALZOLARI, Nicoletta, ed., Frédéric BÉCHET, ed., Philippe BLACHE, ed. and others. Proceedings of the Thirteenth Language Resources and Evaluation Conference. Paris: European Language Resources Association (ELRA), 2022, pp. 3291-3300. ISBN 979-10-95546-72-6

Zusammenfassung

Broadcast political debate is a core pillar of democracy: it is the public’s easiest access to opinions that shape policies and enables the general public to make informed choices. With QT30, we present the largest corpus of analysed dialogical argumentation ever created (19,842 utterances, 280,000 words) and also the largest corpus of analysed broadcast political debate to date, using 30 episodes of BBC’s ‘Question Time’ from 2020 and 2021. Question Time is the prime institution in UK broadcast political debate and features questions from the public on current political issues, which are responded to by a weekly panel of five figures of UK politics and society. QT30 is highly argumentative and combines language of well-versed political rhetoric with direct, often combative, justification-seeking of the general public. QT30 is annotated with Inference Anchoring Theory, a framework well-known in argument mining, which encodes the way arguments and conflicts are created and reacted to in dialogical settings. The resource is freely available at http://corpora.aifdb.org/qt30.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
400 Sprachwissenschaft, Linguistik

Schlagwörter

broadcast political debate, argumentation and conflict, Question Time, Inference Anchoring Theory

Konferenz

Thirteenth Language Resources and Evaluation Conference (LREC 2022), 20. Juni 2022 - 25. Juni 2022, Marseille, France
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ISO 690HAUTLI-JANISZ, Annette, Zlata KIKTEVA, Wassiliki SISKOU, Kamila GORSKA, Ray BECKER, Chris REED, 2022. QT30 : A Corpus of Argument and Conflict in Broadcast Debate. Thirteenth Language Resources and Evaluation Conference (LREC 2022). Marseille, France, 20. Juni 2022 - 25. Juni 2022. In: CALZOLARI, Nicoletta, ed., Frédéric BÉCHET, ed., Philippe BLACHE, ed. and others. Proceedings of the Thirteenth Language Resources and Evaluation Conference. Paris: European Language Resources Association (ELRA), 2022, pp. 3291-3300. ISBN 979-10-95546-72-6
BibTex
@inproceedings{HautliJanisz2022Corpu-66615,
  year={2022},
  title={QT30 : A Corpus of Argument and Conflict in Broadcast Debate},
  url={https://aclanthology.org/2022.lrec-1.352/},
  isbn={979-10-95546-72-6},
  publisher={European Language Resources Association (ELRA)},
  address={Paris},
  booktitle={Proceedings of the Thirteenth Language Resources and Evaluation Conference},
  pages={3291--3300},
  editor={Calzolari, Nicoletta and Béchet, Frédéric and Blache, Philippe},
  author={Hautli-Janisz, Annette and Kikteva, Zlata and Siskou, Wassiliki and Gorska, Kamila and Becker, Ray and Reed, Chris}
}
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Interner Vermerk

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Kontakt
URL der Originalveröffentl.
https://aclanthology.org/2022.lrec-1.352/

Prüfdatum der URL

2023-04-17

Prüfungsdatum der Dissertation

Finanzierungsart

Kommentar zur Publikation

Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Ja
Begutachtet
Link zu Forschungsdaten
http://corpora.aifdb.org/qt30
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