Annotating Attribution in Czech News Server Articles

Barbora Hladka, Jiří Mírovský, Matyáš Kopp, Václav Moravec


Abstract
This paper focuses on detection of sources in the Czech articles published on a news server of Czech public radio. In particular, we search for attribution in sentences and we recognize attributed sources and their sentence context (signals). We organized a crowdsourcing annotation task that resulted in a data set of 2,167 stories with manually recognized signals and sources. In addition, the sources were classified into the classes of named and unnamed sources.
Anthology ID:
2022.lrec-1.193
Volume:
Proceedings of the Thirteenth Language Resources and Evaluation Conference
Month:
June
Year:
2022
Address:
Marseille, France
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
1817–1823
Language:
URL:
https://aclanthology.org/2022.lrec-1.193
DOI:
Bibkey:
Cite (ACL):
Barbora Hladka, Jiří Mírovský, Matyáš Kopp, and Václav Moravec. 2022. Annotating Attribution in Czech News Server Articles. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 1817–1823, Marseille, France. European Language Resources Association.
Cite (Informal):
Annotating Attribution in Czech News Server Articles (Hladka et al., LREC 2022)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingestion-script-update/2022.lrec-1.193.pdf