Martine Hurault-Plantet

Terminological variants for document selection and question/answer matching

Answering precise questions requires applying Natural Language techniques in order to locate the answers inside retrieved documents. The QALC system, presented in this paper, participated to the Question Answering track of the TREC8 and TREC9 evaluations. QALC exploits an analysis of documents based on the search for multi-word terms and their variations. These indexes are used to select a minimal number of documents to be processed and to give indices when comparing question and sentence representations. This comparison also takes advantage of a question analysis module and recognition of numeric and named entities in the documents.

Cooperative requests and replies in a collaborative dialogue model

In this paper, we present a computational model of dialogue, and an underlying theory of action, which supports the representation of, reasoning about and execution of communicative and non-communicative actions. This model rests on a theory of collaborative discourse, and allows for cooperative human?machine communication in written dialogues. We show how cooperative behaviour, illustrated by the analysis of a dialogue corpus and formalized by an underlying theory of cooperation, is interpreted and produced in our model. We describe and illustrate in detail the main algorithms used to model the reasoning processes necessary for interpretation, planning, generation, as well as for determining which actions to perform and when. Finally, we present our implemented system.Our data are drawn from a corpus of human?human dialogues, selected and transcribed from a day-long recording of phone calls at a phone desk in an industrial setting (Castaing, 1993). We present an analysis of this corpus, focusing on dialogues which require, in order to succeed, helpful behaviour on the part of both the caller and the operator.The theoretical framework of our model rests on the theory of collaborative discourse developed by Grosz and Sidner (1986, 1990), Grosz and Kraus (1993, 1996), and further extended by Lochbaum (1994, 1995). An important objective guiding the design of our dialogue model was to allow the agent being modelled to interpret and manifest a type of cooperative behaviour which follows Grosz and Krauss formalization of the commitment of each collaborative agent towards the actions of the other collaborative agents. The model we propose extends Lochbaums approach to discourse processing in extending her interpretation algorithm to allow for the treatment of a wider range of dialogues, and in providing an algorithm of task advancement which guides the generation process and allows for the interleaving of execution and planning, thereby facilitating cooperation among agents. The cooperative behaviour of the agent being modelled rests on the use of communicative actions allowing agents to share additional knowledge and assist each other in performing their actions.

Coping With Alternate Formulations Of Questions And Answers

We present in this chapter the QALC system which has participated in the four TREC QA evaluations. We focus here on the problem of linguistic variation in order to be able to relate questions and answers. We present first, variation at the term level which consists in retrieving questions terms in document sentences even if morphologic, syntactic or semantic variations alter them. Our second subject matter concerns variation at the sentence level that we handle as different partial reformulations of questions. Questions are associated with extraction patterns based on the question syntactic type and the object that is under query. We present the whole system thus allowing situating how QALC deals with variation, and different evaluations.

Two levels of evaluation in a complex NL system

The QALC question-answering system, developed at LIMSI, has been a participant for two years in the QA track of the TREC conference. In this paper, we present a quantitative evaluation of various modules in our system, based on two criteria: first, the numbers of documents containing the correct answer and selected by the system; secondly, the number of answers found. The first criterion is used for evaluating locally the modules in the system, which contribute in selecting documents that are likely to contain the answer. The second one provides a global evaluation of the system. As such, it also serves for an indirect evaluation of various modules.

Communication and Manipulation Acts in a Collaborative Dialogue Model

We present in this chapter a dialogue model and an underlying theory of action that we have developed and tested through an application that simulates a telephone switchboard. The main features of this model are that it rests on a theory of collaborative discourse, and that it allows for the treatment of both communication and manipulation acts. The model thus allows for cooperative human-machine communication in a multimodal context where natural language (in our context typed rather than spoken) is used in combination with direct manipulation.