For people to contribute to discourse, they must do more than utter the right sentence at the right time. The basic requirement is that they odd to their common ground in on orderly way. To do this, we argue, they try to establish for each utterance the mutual belief that the addressees hove understood what the speaker meant well enough for current purposes. This is accomplished by the collective actions of the current contributor and his or her partners, and these result in units of conversation called contributions. We present a model of contributions and show how it accounts for o variety of features of everyday conversations.

This paper presents an algorithm for identifying the noun phrase antecedents of third person pronouns and lexical anaphors (reflexives and reciprocals). The algorithm applies to the syntactic representations generated by McCord's Slot Grammar parser, and relies on salience measures derived from syntactic structure and a simple dynamic model of attentional state. Like the parser, the algorithm is implemented in Prolog. The authors have tested it extensively on computer manual texts, and conducted a blind test on manual text containing 360 pronoun occurrences. The algorithm successfully identifies the antecedent of the pronoun for 86 % of these pronoun occurrences. The relative contributions of the algorithm's components to its overall success rate in this blind test are examined. Experiments were conducted with an enhancement of the algorithm which contributes statistically modelled information concerning semantic and real world relations to the algorithm's decision procedure. Interestingly, this enhancement only marginally improves the algorithm's performance (by 2%). The algorithm is compared with other approaches to anaphora resolution which have been proposed in the literature. In particular, the search procedure of Hobbs ' algorithm was implemented in the Slot Grammar framework and applied to the sentences in the blind test set. The authors ' algorithm achieves a higher rate of success (4%) than Hobbs ' algorithm. The relation of the algorithm to the centering approach is discussed, as well as to models of anaphora resolution which invoke a variety of informational factors in ranking antecedent candidates. 1.

More or less final version. To appear in Natural Language Semantics. According to the alternative semantics for focus, the semantic reflex of intonational focus is a second semantic value, which in the case of a sentence is a set of propositions. We examine a range of semantic and pragmatic applications of the theory, and extract a unitary principle specifying how the focus semantic value interacts with semantic and pragmatic processes. A strong version of the theory has the effect of making lexical or construction-specific stipulation of a focus-related effect in association with focus constructions impossible. Furthermore, while focus has a uniform import, the sources of meaning differences in association with focus are various.

This paper proposes a new theory of the relationship between the sentence processing mechanism and the available computational resources. This theory -- the Syntactic Prediction Locality Theory (SPLT) -- has two components: an integration cost component and a component for the memory cost associated with keeping track of obligatory syntactic requirements. Memory cost is

The Trains project is an effort to build a conversationally proficient planning assistant. A key part of the project is the construction of the Trains system, which provides the research platform for a wide range of issues in natural language understanding, mixedinitiative planning systems, and representing and reasoning about time, actions and events. Four years have now passed since the beginning of the project. Each year we have produced a demonstration system that focused on a dialog that illustrates particular aspects of our research. The commitment to building complete integrated systems is a significant overhead on the research, but we feel it is essential to guarantee that the results constitute real progress in the field. This paper describes the goals of the project, and our experience with the effort so far. This paper is to appear in the Journal of Experimental and Theoretical AI, 1995. The TRAINS project has been funded in part by ONR/ARPA grant N00014-92-J-1512, U.S. Air ...

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We present an algorithm for anaphora resolution which is a modified and extended version of that developed by (Lappin and Leass, 1994). In contrast to that work, our algorithm does not require in-depth, full, syntactic parsing of text. Instead, with minimal compromise in output quality, the modifications enable the resolution process to work from the output of a part of speech tagger, enriched only with annotations of grammatical function of lexical items in the input text stream. Evaluation of the results of our implementation demonstrates that accurate anaphora resolution can be realized within natural language processing frameworks which do not—or cannot—employ robust and reliable parsing components. 1

We present a new method for characterizing the interpretive possibilities generated by elliptical constructions in natural language. Unlike previous analyses, which postulate ambiguity of interpretation or derivation in the full clause source of the ellipsis, our analysis requires no such hidden ambiguity. Further, the analysis follows relatively directly from an abstract statement of the ellipsis interpretation problem. It predicts correctly a wide range of interactions between ellipsis and other semantic phenomena such as quantifier scope and bound anaphora. Finally, although the analysis itself is stated nonprocedurally, it admits of a direct computational method for generating interpretations. This article is available through the Computation and Language E-Print Archive as cmp-lg/9503008, and also appears in Linguistics and Philosophy 14(4):399–452. cmp-lg/9503008 Ellipsis and Higher-Order Unification 1

In a series of papers, Petra Hendriks, Helen de Hoop and Henritte de Swart have applied optimality theory (OT) to semantics. These authors argue that there is a fundamental difference between the form of OT as used in phonology, morphology and syntax on the one hand and its form as used in semantics on the other hand. Whereas in the first case OT takes the point of view of the speaker, in the second case the point of view of the hearer is taken. The aim of this paper is to argue that the proper treatment of OT in natural language interpretation has to take both perspectives at the same time. A conceptual framework is established that realizes the integration of both perspectives. It will be argued that this framework captures the essence of the Gricean maxims and gives a precise explication of Atlas & Levinson`s (1981) idea of balancing between informativeness and efficiency in natural language processing. The ideas are then applied to resolve some puzzles in natural language interpret...

We describe one approach to build an automatically trainable anaphora resolution system. In this approach, we use Japanese newspaper articles tagged with discourse information as training examples for a ms" chine learning algorithm which employs the G4.5 decision tree algorithm by Quinlan (Quinlan, 1993). Then, we evaluate and compare the results of several variants of the machine learning-based approach with those of our existing snaphots resolution system which uses manually-designed knowledge sources. Finally, we compare our algorithms with existing theories of snapbors, in particular, Japanese zero pro- nouns.