This paper considers the problem of automatic assessment of local coherence. We present a novel entity-based representation of discourse which is inspired by Centering Theory and can be computed automatically from raw text. We view coherence assessment as a ranking learning problem and show that the proposed discourse representation supports the effective learning of a ranking function. Our experiments demonstrate that the induced model achieves significantly higher accuracy than a state-of-the-art coherence model. 1

This thesis is an inquiry into the nature of the high-level, rhetorical structure of unrestricted natural language texts, computational means to enable its derivation, and two applications (in automatic summarization and natural language generation) that follow from the ability to build such structures automatically. The thesis proposes a first-order formalization of the high-level, rhetorical structure of text. The formalization assumes that text can be sequenced into elementary units; that discourse relations hold between textual units of various sizes; that some textual units are more important to the writer's purpose than others; and that trees are a good approximation of the abstract structure of text. The formalization also introduces a linguistically motivated compositionality criterion, which is shown to hold for the text structures that are valid. The thesis proposes, analyzes theoretically, and compares empirically four algorithms for determining the valid text structures of ...

This book deals with the semantics of natural language expressions that are commonly taken to refer to individuals: pronouns, definite descriptions and proper names. It claims, contrary to previous theorizing, that they all have a common syntax and semantics, roughly that which is currently associated by philosophers and linguists with definite descriptions as construed in the tradition of Frege. As well as advancing this proposal, I hope to achieve at least one other aim, that of urging semanticists dealing with pronoun interpretation, in particular donkey anaphora, to consider a wider range of theories at all times than is sometimes done at present. I am thinking particularly of the gulf that seems to have emerged between those who practice some version of dynamic semantics (including DRT) and those who eschew this approach and rely on some version of the E-type analysis for donkey anaphora (if they consider this phenomenon at all). In my opinion there is too little work directly comparing the claims of these two schools (for that is what they amount to) and testing them against the data in the way that any two rival theories might be tested. (Irene Heim’s 1990 article in Linguistics and Philosophy does this, and

3.672> X with the complex term 1 + 1, not with 2, which, for people unused to Prolog's little ways, tends to come as a bit of a surprise. If we want to carry out the actual arithmetic involved, we have to explicitly force evaluation by making use of the very special inbuilt `operator' is/2. This calls an inbuilt mechanism which carries out the arithmetic evaluation of its second argument, and then unication plays no role here!). On the other hand, \== checks whether its argument are not identical. Arithmetic Prolog contains some built-in operators for handling integer arithmetic. These include *, / +, - (for multiplication, division, addition, and subtraction, respectively) and >, < for comparing numbers. These symbols, however, are just ordinary Prolog operators. That is, they are just a user friendly notation for writing

We present an algorithm for simultaneously constructing both the syntax and semantics of a sentence using a Lexicalized Tree Adjoining Grammar (LTAG). This approach captures naturally and elegantly the interaction between pragmatic and syntactic constraints on descriptions in a sentence, and the inferential interactions between multiple descriptions in a sentence. At the same

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I propose a model for determining the hearer's attentional state which depends solely on a list of salient discourse entities (S-list). The ordering among the elements of the S-list covers also the function of the backward-looking center in the cen- tering model. The ranking criteria for the S-list are based on the distinction between hearer-old and hearer-new discourse entities and incorporate preferences for inter- and intra-sentential anaphora. The model is the basis for an algorithm which operates incrementally, word by word.

We derive the rhetorical structures of texts by means of two new, surface-form-based algorithms: one that identifies discourse usages of cue phrases and breaks sen- tences into clauses, and one that produces valid rhetorical structure trees for unre- stricted natural language texts. The algo- rithms use information that was derived from a corpus analysis of cue phrases.

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this paper gives a comprehensive picture of a complex, yet not explicitly spelled-out theory of discourse coherence, the centering model (Grosz, Joshi, and Weinstein, 1983, 1995) marked a major step in clarifying the relationship between attentional states and (local) discourse segment structure. More precisely, the centering model accounts for the interactions between local coherence and preferential choices of referring expressions. It relates differences in coherence (in part) to varying demands on inferences as required by different types of referring expressions, given a particular attentional state of the hearer in a discourse setting (Grosz, Joshi, and Weinstein 1995, 204-205). The claim is made then that the lower the inference load put on the hearer, the more coherent the underlying discourse appears. The centering model as formulated by Grosz, Joshi, and Weinstein (1995) refines the structure of "centers" of discourse, which are conceived as the representational device for the attentional state at the local level of discourse. They distinguish two basic types of centers, which can be assigned to each utterance Ui--a single backward- looking center, Cb(Ui), and a partially ordered set of discourse entities, the forward- looking centers, Cf(Ui). The ordering on Cf is relevant for determining the Cb. It can be viewed as a salience ranking that reflects the assumption that the higher the ranking of a discourse entity in Cf, the more likely it will be mentioned again in the immediately following utterance. Thus, given an adequate ordering of the discourse entities in Cf, the costs of computations necessary to establish local coherence are minimized