Moving TIGER beyond Sentence-Level

Agnieszka Falenska, Kerstin Eckart, Jonas Kuhn

Abstract: We present TIGER 2.2-doc -- a new set of annotations for the German TIGER corpus. The set moves the corpus to a document level. It includes a full mapping of sentences to documents, as well as additional sentence-level and document-level annotations. The sentence-level annotations refer to the role of a sentence in the document. They introduce structure to the TIGER documents by separating headers and meta-level information from article content. Document-level annotations recover information which has been neglected in the intermediate releases of the TIGER corpus, such as document categories and publication dates of the articles. Additionally, we introduce new document-level annotations: authors and their gender. We describe the process of corpus annotation, show statistics of the obtained data and present baseline experiments for lemmatization, part-of-speech and morphological tagging, and dependency parsing. Finally, we present two example use cases: sentence boundary detection and authorship attribution. These use cases take the data from TIGER into account and illustrate the usefulness of the new annotation layers from TIGER 2.2-doc.