Definite Clause Grammars (DCGs) have proved valuable to computational linguists since they can be used to specify phrase structured grammars. It is well known how to encode DCGs in Horn clauses. Some linguistic phenomena, such as filler-gap dependencies, are difficult to account for in a completely satisfactory way using simple phrase structured grammar. In the literature of logic grammars there have been several attempts to tackle this problem by making use of special arguments added to the DCG predicates corresponding to the grammatical symbols. In this paper we take a different line, in that we account for filler-gap dependencies by encoding DCGs within hereditary Harrop formulas, an extension of Horn clauses (proposed elsewhere as a foundation for logic programming) where implicational goals and universally quantified goals are permitted. Under this approach, filler-gap dependencies can be accounted for in terms of the operational semantics underlying hereditary Harrop formulas, in a way reminiscent of the treatment of such phenomena in Generalized Phrase Structure Grammar (GPSG). The main features involved in this new formulation of DCGs are mechanisms for providing scope to constants and program clauses along with a mild use of λ-terms and λ-conversion. 1

This paper presents a formal `fragment' of database semantics as a declarative model of a cognitive agent. It is called a SLIM machine and functionally integrates the procedures of natural language interpretation, conceptualization, and production as well as query and inference. Each of these functions is illustrated explicitly by a corresponding LA-grammar. In addition, a control structure based on the principle of balance is presented. This principle mediates between the knowledge of the SLIM machine and its current situation by selecting a suitable action. # 2001 Elsevier Science B.V. All rights reserved.

Abstract. A model for context-dependent natural language semantics is proposed and formalized in terms of possible worlds. The meaning of a sentence depends on context and at the same time affects that context representing the knowledge about the world collected from a discourse. The model fits well with a “flat ” semantic representation as first proposed by Hobbs (1985), consisting basically of a conjunction of atomic predications in which all variables are existentially quantified with the widest possible scope; in our framework, this provides very concise semantic terms as compared with other representations. There is a natural correspondence between the possible worlds semantics and a constraint solver, and it is shown how such a semantics can be defined using the programming language of Constraint Handling Rules (Frühwirth, 1995). Discourse analysis is clearly a process of abduction in this framework, and it is shown that the mentioned constraint solvers serve as effective and efficient abductive engines for the purpose. 1

Abstract. Meaning is a marvellous and dreadful matter, as it is neither totally intelligible nor totally unintelligible. It cannot be considered as an univocal, closed and fixed entity, atomic in nature, universally shared and invariable in time. Rather, meaning has a complex design, composed by different facets: a referential, an inferential, and a differential one. This standpoint, which overcomes the truth-conditional semantics as well as the structural one, entails that meaning is patterned in nature, based on the encyclopaedic knowledge and connected with mental concepts. The meaning dilemma between variability and stability is crucial for every semantic theory, as meaning flexibility, grounded on the daily experience, displays a large range of linguistic phenomena like the defeasibility of semantic traits, fuzzy boundaries, radial categorization, semantic gradualness and polysemy, the interconnection between the literal and non-literal semantic domain as well as the context dependence. The semantic variability calls for an inferential process, as modal meaning is not an immediate and fully evident datum; rather, it is generated by communicators during their interaction

Predicate calculus treats determiner-noun sequences like the man, every man, orseveral men as ‘quantified noun phrases.’ This analysis in terms of quantifiers, variables, and connectives creates a major structural difference compared to the handling of proper names. The modeling of natural language communication in database semantic (DBS), in contrast, treats the functorargument structure as primary, regardless of whether an argument is of the sign type symbol (determiner-noun sequence), name, or indexical (pronoun). In this paper, the meanings carried by different determiners are reanalyzed as controlling the internal matching between nominal symbols and individuals, or sets of individuals, at the level of context.