The main contributions of this thesis are as follows:
1. We introduce a general model for coreference and explore its application to German.
• The model features an incremental discourse processing algorithm which allows it to coherently address issues caused by underspecification of mentions, which is an especially pressing problem regarding certain German pronouns.
• We introduce novel features relevant for the resolution of German pronouns. A subset of these features are made accessible through the incremental architecture of the discourse processing model.
• In evaluation, we show that the coreference model combined with our features provides new state-of-the-art results for coreference and pronoun resolution for German.
2. We elaborate on the evaluation of coreference and pronoun resolution.
• We discuss evaluation from the view of prospective downstream applications that benefit from coreference resolution as a preprocessing component. Addressing the shortcomings of the general evaluation framework in this regard, we introduce an alternative framework, the Application Related Coreference Scores (ARCS).
• The ARCS framework enables a thorough comparison of different system outputs and the quantification of their similarities and differences beyond the common coreference evaluation. We demonstrate how the framework is applied to state-of-the-art coreference systems. This provides a method to track specific differences in system outputs, which assists researchers in comparing their approaches to related work in detail.
3. We explore semantics for pronoun resolution.
• Within the introduced coreference model, we explore distributional approaches to estimate the compatibility of an antecedent candidate and the occurrence context of a pronoun. We compare a state-of-the-art approach for word embeddings to syntactic co-occurrence profiles to this end.
• In comparison to related work, we extend the notion of context and thereby increase the applicability of our approach. We find that a combination of both compatibility models, coupled with the coreference model, provides a large potential for improving pronoun resolution performance.
We make available all our resources, including a web demo of the system, at: http://pub.cl.uzh.ch/purl/coreference-resolution