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
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 1817–1823
- Language:
- URL:
- https://aclanthology.org/2022.lrec-1.193
- DOI:
- 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)
- PDF:
- https://preview.aclanthology.org/naacl24-info/2022.lrec-1.193.pdf