Annotating Attribution in Czech News Server Articles

Proceedings of the Thirteenth International Conference on Language Resources and Evaluation (LREC 2022)

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.