Selectional Restrictions in HPSG

Selectional restrictions are semantic sortal constraints imposed on the participants of linguistic constructions to capture contextually-dependent constraints on interpretation. Despite their limitations, selectional restrictions have proven very useful in natural language applications, where they have been used frequently in word sense disambiguation, syntactic disambiguation, and anaphora resolution. Given their practical value, we explore two methods to incorporate selectional restrictions in the HPSG theory, assuming that the reader is familiar with HPSG. The first method employs HPSG's Background feature and a constraint-satisfaction component pipe-lined after the parser. The second method uses subsorts of referential indices, and blocks readings that violate selectional restrictions during parsing. While theoretically less satisfactory, we have found the second method particularly useful in the development of practical systems.

The Role of the Gricean Maxims in the Generation of Referring Expressions

Grice's maxims of conversation [Grice 1975] are framed as directives to be followed by a speaker of the language. This paper argues that, when considered from the point of view of natural language generation, such a characterisation is rather misleading, and that the desired behaviour falls out quite naturally if we view language generation as a goal-oriented process. We argue this position with particular regard to the generation of referring expressions.

Generating One-Anaphoric Expressions: Where Does the Decision Lie?

Most natural language generation systems embody mechanisms for choosing whether to subsequently refer to an already-introduced entity by means of a pronoun or a definite noun phrase. Relatively few systems, however, consider referring to entites by means of one-anaphoric expressions such as \lingform{the small green one}. This paper looks at what is involved in generating referring expressions of this type. Consideration of how to fit this capability into a standard algorithm for referring expression generation leads us to suggest a revision of some of the assumptions that underlie existing approaches. We demonstrate the usefulness of our approach to one-anaphora generation in the context of a simple database interface application, and make some observations about the impact of this approach on referring expression generation more generally.

Computational Interpretations of the Gricean Maxims in the Generation of Referring Expressions

We examine the problem of generating definite noun phrases that are appropriate referring expressions; i.e, noun phrases that (1) successfully identify the intended referent to the hearer whilst (2) not conveying to her any false conversational implicatures (Grice, 1975). We review several possible computational interpretations of the conversational implicature maxims, with different computational costs, and argue that the simplest may be the best, because it seems to be closest to what human speakers do. We describe our recommended algorithm in detail, along with a specification of the resources a host system must provide in order to make use of the algorithm, and an implementation used in the natural language generation component of the IDAS system. This paper will appear in the the April--June 1995 issue of Cognitive Science, and is made available on cmp-lg with the permission of Ablex, the publishers of that journal.