Enhancing character type detection using coreference information : experiments on dramatic texts

Abstract

This thesis describes experiments on enhancing machine-learning based detection of literary character types in German-language dramatic texts by using coreference information. The thesis makes four major contributions to the research discourse of character type detection and coreference resolution for German dramatic texts: (i) a corpus of annotations of coreference on dramatic texts, called GerDraCor-Coref, (ii) a rule-based system to automatically resolve coreferences on dramatic texts, called DramaCoref, as well as experiments and analyses of results by using DramaCoref on GerDraCor-Coref, (iii) experiments on the automatic detection of three selected character types (title characters, protagonists and schemers) using machine-learning approaches, and (iv) experiments on utilizing the coreference information of (i) and (ii) for improving the performance of character type detection of (iii).