Abstract
This paper reports on a study of the inter-annotation agreement to assess the manual annotation of the TAGFACT Gold Standard corpus. This corpus has been created as part of a larger project (TAGFACT), whose final objective is to automatize the classification of the factual status of events in a corpus of Spanish journalistic texts. In our study, six annotators labeled a corpus using the four levels of linguistic description proposed in our project to extract factual information. Each one of these levels has been assessed independently. As expected, the more fine-grained the classification is, the more problematic the annotation. This study identifies some of the most important differences and discusses the main problems encountered to obtain full agreement. We use Cohenâs Kappa to measure inter-annotation agreement as well as descriptive statistical analysis.
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