Bonnie Webber

Structure and ostension in the interpretation of discourse deixis

Abstract This paper examines demonstrative pronouns used as deictics to refer to the interpretation of one or more clauses. Although this usage is frowned upon in style manuals (for example Strunk and White (1959) state that “This. The pronoun this, referring to the complete sense of a preceding sentence or clause, cannot always carry the load and so may produce an imprecise statement”), it is nevertheless very common in written text. Handling this usage poses a problem for Natural Language Understanding systems. The solution I propose is based on distinguishing between what can be pointed to and what can be referred to by virtue of pointing. I argue that a restricted set of discourse segments yield what such demonstrative pronouns can point to in the discourse model and a restricted set of what Nunberg (1979) has called referring functions yield what they can refer to by virtue of that pointing.

Anaphora and Discourse Structure

We argue in this article that many common adverbial phrases generally taken to signal a discourse relation between syntactically connected units within discourse structure instead work anaphorically to contribute relational meaning, with only indirect dependence on discourse structure. This allows a simpler discourse structure to provide scaffolding for compositional semantics and reveals multiple ways in which the relational meaning conveyed by adverbial connectives can interact with that associated with discourse structure. We conclude by sketching out a lexicalized grammar for discourse that facilitates discourse interpretation as a product of compositional rules, anaphor resolution, and inference.

Microplanning with Communicative Intentions: The SPUD System

The process of microplanning in natural language generation (NLG) encompasses a range of problems in which a generator must bridge underlying domain‐specific representations and general linguistic representations. These problems include constructing linguistic referring expressions to identify domain objects, selecting lexical items to express domain concepts, and using complex linguistic constructions to concisely convey related domain facts.

DISCOURSE DEIXIS: REFERENCE TO DISCOURSE SEGMENTS

Computational approaches to discourse understanding have a two-part goal: (1) to identify those aspects of discourse understanding that require process-based accounts, and (2) to characterize the processes and data structures they involve. To date, in the area of reference, process-based accounts have been developed for subsequent reference via anaphoric pronouns and reference via definite descriptors. In this paper, I propose and argue for a process-based account of subsequent reference via deictic expressions. A significant feature of this account is that it attributes distinct mental reality to units of text often called discourse segments, a reality that is distinct from that of the entities described therein.

Discourse structure and language technology

An increasing number of researchers and practitioners in Natural Language Engineering face the prospect of having to work with entire texts, rather than individual sentences. While it is clear that text must have useful structure, its nature may be less clear, making it more difficult to exploit in applications. This survey of work on discourse structure thus provides a primer on the bases of which discourse is structured along with some of their formal properties. It then lays out the current state-of-the-art with respect to algorithms for recognizing these different structures, and how these algorithms are currently being used in Language Technology applications. After identifying resources that should prove useful in improving algorithm performance across a range of languages, we conclude by speculating on future discourse structure-enabled technology.

D-LTAG System: Discourse Parsing with a Lexicalized Tree-Adjoining Grammar

We present an implementation of a discourse parsing system for alexicalized Tree-Adjoining Grammar for discourse, specifying the integrationof sentence and discourse level processing. Our system is based on theassumption that the compositional aspects of semantics at thediscourse level parallel those at the sentence level. This coupling isachieved by factoring away inferential semantics and anaphoric features ofdiscourse connectives. Computationally, this parallelism is achievedbecause both the sentence and discourse grammar are LTAG-based and the sameparser works at both levels. The approach to an LTAG for discourse has beendeveloped by Webber and colleagues in some recent papers. Our system takes a discourseas input, parses the sentences individually, extracts the basic discourseconstituent units from the sentence derivations, and reparses the discoursewith reference to the discourse grammar while using the same parser usedat the sentence level.

Discourse Relations: A Structural and Presuppositional Account Using Lexicalised TAG

We show that discourse structure need not bear the full burden of conveying discourse relations by showing that many of them can be explained nonstructurally in terms of the grounding of anaphoric presuppositions (Van der Sandt, 1992). This simplifies discourse structure, while still allowing the realisation of a full range of discourse relations. This is achieved using the same semantic machinery used in deriving clause-level semantics.

Attribution and the (Non-)Alignment of Syntactic and Discourse Arguments of Connectives

The annotations of the Penn Discourse Treebank (PDTB) include (1) discourse connectives and their arguments, and (2) attribution of each argument of each connective and of the relation it denotes. Because the PDTB covers the same text as the Penn TreeBank WSJ corpus, syntactic and discourse annotation can be compared. This has revealed significant differences between syntactic structure and discourse structure, in terms of the arguments of connectives, due in large part to attribution. We describe these differences, an algorithm for detecting them, and finally some experimental results. These results have implications for automating discourse annotation based on syntactic annotation.

Genre distinctions for discourse in the Penn TreeBank

Articles in the Penn TreeBank were identified as being reviews, summaries, letters to the editor, news reportage, corrections, wit and short verse, or quarterly profit reports. All but the latter three were then characterised in terms of features manually annotated in the Penn Discourse TreeBank --- discourse connectives and their senses. Summaries turned out to display very different discourse features than the other three genres. Letters also appeared to have some different features. The two main findings involve (1) differences between genres in the senses associated with intra-sentential discourse connectives, inter-sentential discourse connectives and inter-sentential discourse relations that are not lexically marked; and (2) differences within all four genres between the senses of discourse relations not lexically marked and those that are marked. The first finding means that genre should be made a factor in automated sense labelling of non-lexically marked discourse relations. The second means that lexically marked relations provide a poor model for automated sense labelling of relations that are not lexically marked.

Flexible support for trauma management through goal-directed reasoning and planning

We describe a system, TRAUMAID, which has been designed to provide decision support throughout the initial definitive management of severely injured patients (i.e. after their initial evaluation, resuscitation, and stabilization). Over the course of initial definitive management, TraumAID recommends appropriate procedures to be carried out, based on currently available evidence and on the complexity and urgency of the situation. TraumAIDs ability to deal flexibly with complex and often urgent situations comes from its ability to reason separately about the management goals that should be achieved and about the means that are situationally appropriate for achieving them. In this paper, we describe TraumAIDs approach to trauma management in more detail, showing in particular how it enables TraumAID to adapt its reasoning and recommendations to the urgency with which a patients condition must be addressed.