... this paper, we argue that, to handle explanation dialogues successfully, a discourse model must include information about the intended effect of individual parts of the text on the hearer, as well as how the parts relate to one another rhetorically. We present a text planner that records this information and show how the resulting structure is used to respond appropriately to a follow-up question.

This paper describes the linguistic part of a system called PROVERB, which transforms, abstracts, and verbalizes machine-found proofs into formated texts. Linguistically, the architecture of PROVERB follows most application oriented systems, and is a pipe-lined control of three components. Its macroplanner linearizes a proof and plans mediating communicative acts by employing a combination of hierarchical planning and focus-guided navigation. The microplanner

This thesis develops a new approach to automatic language generation that focuses on the need to produce a range of different paraphrases from the same input representation. One novelty of the system is its solidly grounding representations of word meaning in a background knowledge base, which enables the production of paraphrases stemming from certain inferences, rather than from purely lexical relationships alone. The system is designed in such a way that the paraphrasing mechanism extends naturally to a multilingual generator; specifically, we will be concerned with producing English and German sentences. The focus of the system is on lexical paraphrases, and one of the contributions of the thesis is in identifying, analyzing and extending relevant linguistic research so that it can be used to handle...

The acceptance of natural language generation systems strongly depends on their capability to facilitate the exchange of information with human users. Current generation systems consider the influence of situational factors on the content and the form of the resulting utterances. However, the need to time their processing flexibly is usually neglected although temporal factors play a central part when directly addressing a human communication partner. A short response time of a system is crucial for its effective use. Furthermore, some applications --- e.g., the simultaneous description of ongoing events --- even necessitate the interleaving of input consumption and output production, i.e. the use of an incremental processing mode. We claim that incremental processing is a central design principle for developing flexible and efficient generators for speech output. We discuss the advantages of parallel processing for incremental generation and several aspects of control of the generator...

We argue that .the current, predominantly task-oriented, approaches to modularizing text 'generation, While plausible and useful conceptually, set up spurious conceptual and operational constraints. We propose a data-driven approach to modularization and illustrate how it eliminates.

During the planning of multimedia presentations, at least two distinct processes are required: planning the underlying discourse structure (that is, ordering and interrelating the information to be presented) and allocating the media (that is, delimiting the portions to be displayed by each individual medium). The former process has been the topic of several studies in the area of text planning, but numerous questions remain for the latter, including: What is the nature of the allocation process --- what does it start with and what does it produce? What information does it depend on? How should the two processes be performed --- sequentially, interleaved, or simultaneously? In this paper, we define Discourse Structure and Presentation Structure and outline the kinds of information that media allocation rules must depend on, including, centrally, information about the discourse structure. We describe a prototype planning system that performs the information-to-media allocation, arguing ...

This paper outlines an implemented system called PROVERB that explains machine-found natural deduction proofs in natural language. Different from earlier works, we pursue a reconstructive approach. Based on the observation that natural deduction proofs are at a too low level of abstraction compared with proofs found in mathematical textbooks, we define first the concept of socalled assertion level inference rules. Derivations justified by these rules can intuitively be understood as the application of a definition or a theorem. Then an algorithm is introduced that abstracts machine-found ND proofs using the assertion level inference rules. Abstracted proofs are then verbalized into natural language by a presentation module. The most significant feature of the presentation module is that it combines standard hierarchical text planning and techniques that locally organize argumentative texts based on the derivation relation under the guidance of a focus mechanism. The behavior of the s...

This paper deals with the reference choices involved in the generation of argumentative text. Since a natual segmentation of discourse into attentional spaces is needed to carry out this task, this paper first proposes an architecture for natural language generation that combines hierarchical planning and focus-guided navigation, a work in its own right. While hierarchical planning spans out an attentional hierarchy of the discourse produced, local navigation fills details into the primitive discourse spaces. The usefulness of this architecture actually goes beyond the particular domain of application for which it is developed. A piece of argumentative text such as the proof of a mathematical theorem conveys a sequence of derivations. For each step of derivation, the premises derived in the previous context and the inference method (such as the application of a particular theorem or definition) must be made clear. Although not restricted to nominal phrases, our reference decisions are similar to those concerning nominal subsequent referring expressions. Based on the work of Reichmann, this paper presents a discourse theory that handles reference choices by taking into account both textual distance as well as the attentional hierarchy.

This paper presents a formal `fragment' of database semantics as a declarative model of a cognitive agent. It is called a SLIM machine and functionally integrates the procedures of natural language interpretation, conceptualization, and production as well as query and inference. Each of these functions is illustrated explicitly by a corresponding LA-grammar. In addition, a control structure based on the principle of balance is presented. This principle mediates between the knowledge of the SLIM machine and its current situation by selecting a suitable action. # 2001 Elsevier Science B.V. All rights reserved.

this paper we focus on the application of description logics to natural language processing. In cooperation with the pracma Project