Selectional constraints are limitations on the applicability of predicates to arguments. For example, the statement “The number two is blue” may be syntactically well formed, but at some level it is anomalous — BLUE is not a predicate that can be applied to numbers. According to the influential theory of (Katz and Fodor, 1964), a predicate associates a set of defining features with each argument, expressed within a restricted semantic vocabulary. Despite the persistence of this theory, however, there is widespread agreement about its empirical shortcomings (McCawley, 1968; Fodor, 1977). As an alternative, some critics of the Katz-Fodor theory (e.g. (Johnson-Laird, 1983)) have abandoned the treatment of selectional constraints as semantic, instead treating them as indistinguishable from inferences made on the basis of factual knowledge. This provides a better match for the empirical phenomena, but it opens up a different problem: if selectional constraints are the same as inferences in general, then accounting for them will require a much more complete understanding of knowledge representation and inference than we have at present. The problem, then, is this: how can a theory of selectional constraints be elaborated without first having either an empirically adequate theory of defining features or a comprehensive theory of inference? In this dissertation, I suggest that an answer to this question lies in the representation of conceptual

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An approach for guiding the construction of use case specifications is presented. A use case specification comprises contextual information of the use case, its change history, the complete graph of possible pathways, attached requirements and open issues. The proposed approach delivers a use case specification as an unambiguous natural language text. This is done by a stepwise and guided process which progressively transforms initial and partial natural language descriptions of scenarios into well structured, integrated use case specifications. The basis of the approach is a set of linguistic patterns and linguistic structures. The former constitutes the deep structure of the use case specification whereas the latter corresponds to the surface structures. The paper presents the use case model, the linguistic basis and the guided process along with the associated guidelines and support rules. The process is illustrated with the automated teller machine (ATM) case study.

This paper brings a logical perspective to the generation of referring expressions, addressing the incompleteness of existing algorithms in this area. After studying references to individual objects, we discuss references to sets, including Boolean descriptions that make use of negated and disjoined properties. To guarantee that a distinguishing description is generated whenever such descriptions exist, the paper proposes generalizations and extensions of the Incremental Algorithm of Dale and Reiter (1995). 1. Introduction Generation of referring expressions (GRE) is a key task of most Natural Language Generation (NLG) systems (e.g., Reiter and Dale (2000), section 5.4). Regardless of the type of Knowledge Base (KB) forming the input to the generator, many objects will tend to be designated in it using the technical jargon of computerized databases. Such jargon can be difficult to understand. This is true, for example,

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I explore some of the issues that arise when trying to establish a connection between the underspecification hypothesis pursued in the NLP literature and work on ambiguity in semantics and in the psychological literature. A theory of underspecification is developed `from the first principles', i.e., starting from a definition of what it means for a sentence to be semantically ambiguous and from what we know about the way humans deal with ambiguity. An underspecified language is specified as the translation language of a grammar covering sentences that display three classes of semantic ambiguity: lexical ambiguity, scopal ambiguity, and referential ambiguity. The expressions of this language denote sets of senses. A formalization of defeasible reasoning with underspecified representations is presented, based on Default Logic. Some issues to be confronted by such a formalization are discussed. 1 The Combinatorial Explosion Puzzle The alternative syntactic readings of a sen...

The use of logic to model the information retrieval process has become an established research area. Nevertheless, many people in the information retrieval community do not yet appreciate the work performed in this area, mainly because they do not understand logical formalisms, and hence cannot see the connection between logic and information retrieval. This paper aims at resolving the problem. It introduces the formalisms used in logical models for information retrieval, shows the use of logic to build the models, and presents a brief overview of some of the current logical models in information retrieval. 2 1 INTRODUCTION It has been argued that current information retrieval (IR) models offer only simplistic and specific representations of information (Chiaramella and Chevallet, 1992, Nie, 1990, van Rijsbergen, 1989). There is, therefore, a need for the development of a new formalism able to model IR systems in a more generic manner, hence capturing information as it appear...

We describe a knowledge representation and inference formalism, based on an intensional propositional semantic network, in which variables are structured terms consisting of quantifier, type, and other information. This has three important consequences for natural language processing. First, this leads to an extended, more "natural" formalism whose use and representations are consistent with the use of variables in natural language in two ways: the structure of representations mirrors the structure of the language and allows re-use phenomena such as pronouns and ellipsis. Second, the formalism allows the specification of description subsumption as a partial ordering on related concepts (variable nodes in a semantic network) that relates more general concepts to more specific instances of that concept, as is done in language. Finally, this structured variable representation simplifies the resolution of some representational difficulties with certain classes of natural language sentences...

We propose a unified flamework in which to treat semantic underspecification and parallelism phenomena in discourse. The framework employs a constraint language that can express equality and subtree relations between finite trees. In addition, our constraint language can express the equality up-to relation over trees which captures parallelism between them. The constraints are solved by context unification. We demonstrate the use of our framework at the examples of quantifier scope, ellipsis, and their interaction. 1 I

Abstract. One of the key properties of (natural) languages is that they are hierarchical. Phrases combine into larger phrases eventually covering complete sentences. The semantics of each phrase combine to form the complex meaning of the whole. A key question in explaining the origins and evolution of language is therefore how such hierarchical structures may originate and spread in a population. This paper reports on breakthrough experiments in which unbounded hierarchical structure can emerge as a side-effect of repair strategies in a population of agents. 1