Information Structure in Discourse
The present dissertation proposes integrating Discourse Representation Theory (DRT), information structure (IS) and Combinatory Categorial Grammar (CCG) into a single framework. It achieves this by making two new contributions to computational treatment of information structure. First, it presents an uncomplicated approach to incorporating information structure in DRT. Second, it shows how the new DRT representation can be integrated into a unification-based grammar framework in a straightforward manner. We foresee the main application of the new formalism to be in spoken language systems: the approach presented here has the potential to considerably facilitate spoken language systems benefiting from insights derived from information structure. The DRT representation with information structure which is proposed in this dissertation is simpler than the previous attempts to include information structure in DRT. We believe that the simplicity of the Information-Structure-marked Discourse Representation Structure (IS-DRS) is precisely what makes it attractive and easy to use for practical tasks like determining the intonation in spoken language applications. The IS component in ISDRS covers a range of aspects of information structural semantics. A further advantage of IS-DRS is that in its case a single semantic representation is suitable for both the generation of context-appropriate prosody and automatic reasoning. A semantic representation on its own is useful for describing and analysing a language. However, it is of even greater utility if it is accompanied by a mechanism that allows one to directly infer the semantic representation from a natural language expression. We incorporated the IS-DRS into the Categorial Grammar (CG) framework, developing a unification based realisation of Combinatory Categorial Grammar, which we call Unification-based Combinatory Categorial Grammar (UCCG). UCCG inherits elements from Combinatory Categorial Grammar and Unification Categorial Grammar. The UCCG framework is developed gradually throughout the dissertation. The information structural component is included as the final step. The IS-DRSs for linguistic expressions are built up compositionally from the IS-DRSs of their sub-expressions. Feature unification is the driving force in this process. The formalism is illustrated by numerous examples which are characterised by different levels of syntactic complexity and diverse information structure. We believe that the main assets of both the IS-DRSs as well as the Unification-based Combinatory Categorial Grammar framework are their simplicity, transparency, and inherent suitability for computational implementation. This makes them an appealing choice for use in practical applications like spoken language systems.