this paper, we focus on two levels of analysis. The first involves the relation between the information conveyed in consecutive elements of a coherent discourse. Thus, for example, one utterance may describe an event that can be presumed to be the cause of another event described in the subsequent utterance. This causal relation is at what we will call the informational level. The second level of relation results from the fact that discourses are produced to effect changes in the mental state of the discourse participants. In coherent discourse, a speaker is carrying out a consistent plan to achieve the intended changes, and consecutive discourse elements are related to one another by means of the ways in which they participate in that plan. Thus, one utterance may be intended to increase the likelihood that the hearer will come to * Department of Computer Science and Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA 15260. e-mail: jmoore,pollackcs.pitt.edu 1 In addition, intentional structure is needed to make certain types of choices during the generation process, e.g., how to refer to an object (Appelt 1985)

Centering was formulated as a model of the relationship between attentional state, the form of referring expressions, and the coherence of an utterance within a discourse segment (Grosz, Joshi and Weinstein, 1986; Grosz, Joshi and Weinstein, 1995). In this chapter, I argue that the restriction of centering to operating within a discourse segment should be abandoned in order to integrate centering with a model of global discourse structure. The within-segment restriction causes three problems. The first problem is that centers are often continued over discourse segment boundaries with pronominal referring expressions whose form is identical to those that occur within a discourse segment. The second problem is that recent work has shown that listeners perceive segment boundaries at various levels of granularity. If centering models a universal processing phenomenon, it is implausible that each listener is using a different centering algorithm.The third issue is that even for utterances within a discourse segment, there are strong contrasts between utterances whose adjacent utterance within a segment is hierarchically recent and those whose adjacent utterance within a segment is linearly recent. This chapter argues that these problems can be eliminated by replacing Grosz and Sidner's stack model of attentional state with an alternate model, the cache model. I show how the cache model is easily integrated with the centering algorithm, and provide several types of data from naturally occurring discourses that support the proposed integrated model. Future work should provide additional support for these claims with an examination of a larger corpus of naturally occurring discourses.

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In this paper, we propose a generalization of Centering Theory (CT) (Grosz, Joshi, Weinstein (1995)) called Veins Theory (VT), which extends the applicability of centering rules from local to global discourse. A key facet of the theory involves the identification of "veins" over discourse structure trees such as those defined in RST, which delimit domains of referential accessibility for each unit in a discourse. Once identified, reference chains can be extended across segment boundaries, thus enabling the application of CT over the entire discourse. We describe the processes by which veins are defined over discourse structure trees and how CT can be applied to global discourse by using these chains. We also define a discourse "smoothness" index which can be used to compare different discourse structures and interpretations, and show how VT can be used to abstract a span of text in the context of the whole discourse. Finally, we validate our theory by analyzing examples from corpora of English, French, and Romanian.

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Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233 B.2 Portions of the Interlingua Representation . . . . . . . . . . . . . . . . . . . 236 B.3 Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 246 viii List of Tables 4.1 The Three Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 ix List of Figures 1.1 Parse Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 1.2 Combination Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 1.3 Repair Hypotheses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 3.1 Combination Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 4.1 Sample Partial Parse . . . . . . . . . . . . . . . . . . . . . . . . . . .

In order to provide a principled foundation for the study of discourse, in this paper we propose answers to three basic questions: What are the atomic units of discourse? What kind of structures can be built from the elementary units? How do we interpret the resulting structures semantically? Inferences and the correct interpretation of deixis and anaphors in discourse depend upon both structural and semantic accessibility relations. Structurally, we argue, discourse is context free and accessibility is determined by the coordination and subordination relations specified by the model of discourse presented here. Semantically, accessibility is controlled by relations among a number of modal contexts (interaction, speech event, genre unit, modality, polarity, and point of view) which determine the discourse world relative to which each primitive discourse unit is interpreted. To demonstrate the validity of our approach, the linguistic discourse model developed here is applied to a problem concerning the distribution of a discourse particle in Mocho and to various problems of discourse interpretation.

Most coreference resolution models determine if two mentions are coreferent using a single function over a set of constraints or features. This approach can lead to incorrect decisions as lower precision features often overwhelm the smaller number of high precision ones. To overcome this problem, we propose a simple coreference architecture based on a sieve that applies tiers of deterministic coreference models one at a time from highest to lowest precision. Each tier builds on the previous tier’s entity cluster output. Further, our model propagates global information by sharing attributes (e.g., gender and number) across mentions in the same cluster. This cautious sieve guarantees that stronger features are given precedence over weaker ones and that each decision is made using all of the information available at the time. The framework is highly modular: new coreference modules can be plugged in without any change to the other modules. In spite of its simplicity, our approach outperforms many state-of-the-art supervised and unsupervised models on several standard corpora. This suggests that sievebased approaches could be applied to other NLP tasks. 1

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Computational theories of discourse are concerned with the context-based interpreta-tion or generation of discourse phenomena in text and dialogue. In the past, research in