Constraint Solving and Language Processing 

Abstract: Formal models of natural language semantics using TTR Type Theory with Records attempt to relate natural language to perception, modelled as classification of objects and events by types which are available as resources to an agent. We argue that this is better suited for representing the meaning of spatial descriptions in the context of agent modelling than traditional formal semantic models which do not relate spatial concepts to perceptual apparatus. Spatial descriptions include perceptual, conceptual and discourse knowledge which we represent all in a single framework. Being a general framework for modelling both linguistic and non-linguistic cognition, TTR is more suitable for the modelling of situated conversational agents in robotics and virtual environments where interoperability between language, action and perception is required. The perceptual systems gain access to abstract conceptual meaning representations of language while the latter can be justified in action and perception.

Abstract: To formalize and analyze the role of animacy information in on-line sentence comprehension, results of several on-line studies are compared and analyzed according to a new model of incremental optimization of interpretation. This model makes use of violable ranked constraints. To analyze the use of animacy information a set of four constraints is needed, namely Case, Selection, Precedence, and Prominence. It is shown that the pattern of constraint violations of these four constraints provide sufficient information to reflect the on-line effects of language comprehension studies in which animacy information played a crucial role. More specifically, the evaluation of sentences in which either case information or animacy information in combination with the selection restrictions of the verb were used, showed that the model can account for the ambiguity resolution with both sorts of information. The model was also successfully applied to the on-line processing of a more complex object relative structure in English.

Abstract: We discuss the semantics of NL coordination in modern type theories MTTs with coercive subtyping. The issue of conjoinable types is handled by means of a type universe of linguistic types. We discuss quantifier coordination, arguing that they should be allowed in principle and that the semantic infelicity of some cases of quantifier coordination is due to the incompatible semantics of the relevant quantifiers. Non-Boolean collective readings of conjunction are also discussed and, in particular, treated as involving the vectors of type VecA,n, an inductive family of types in an MTT. Lastly, the interaction between coordination and copredication is briefly discussed, showing that the proposed account of coordination and that of copredication by means of dot-types combine consistently as expected.

Abstract: We present a parser for German that achieves a competitive accuracy on unrestricted input while maintaining a coverage of 100%. By writing well-formedness rules as declarative, defeasible constraints that integrate different sources of linguistic knowledge, very high robustness is achieved against all sorts of extragrammatical constructions.