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<Paper uid="C04-1170">
  <Title>Kaplan, J., Cooperative Responses from a Portable</Title>
  <Section position="2" start_page="0" end_page="0" type="intro">
    <SectionTitle>
1 Motivations
</SectionTitle>
    <Paragraph position="0"> The framework of Advanced Question Answering (QA) systems, including cooperative QA answering, as described in a recent road map (Voorees 2003), raises new challenges for language generation since answers are often produced via dedicated inference mechanisms operating over various knowledge sources, including conceptual ontologies. Producing well-formed and informative responses gives a whole new insight to language generation, and in particular to the difficult problem of lexicalisation.</Paragraph>
    <Paragraph position="1"> For example, the question: A bungalow in Meg`eve for 15 persons ? has the response: There are no bungalows in Meg`eve, we can propose you 2 close-by chalets or a country cottage for 15 persons in Meg`eve, or a 15 person bungalow in les Houches (8kms) or in Acacias (12kms), where closely related alternatives are proposed on: (1) sister concepts of bungalow (the question focus): a country cottage or 2 close-by chalets (assuming a chalet capacity does not exceed 10 persons) in the same village or (2) sister concepts of the Meg`eve village (the strongest constraint on the focus): close-by villages where bungalows meet the 15 person constraint. The response involves evaluating village proximity and sorting responses, e.g. by increasing distance from Meg`eve. The first part of the response There are no bungalows in Meg`eve is the direct response, which corrects the user false presupposition, while the remainder of the response reflects the cooperative know-how of the responder. Cooperative know-how involves several forms of responses that include relaxations, intensional calculus, expression of restrictions, of warnings and conditional responses (Benamara et al. 2004).</Paragraph>
    <Paragraph position="2"> This simple example shows that, if a direct response cannot be found, several forms of knowledge and reasoning schemas need to be used and that the NL form of the response requires adequate and subtle lexicalisations, often directed by the reasoning schemas.</Paragraph>
    <Paragraph position="3"> Lexicalisation is the operation that associates a word or an expression to a concept. It is a major parameter in response production (Reiter et Dale, 1997), (a good synthesis can be found in (Cahill, 1999)). Lexicalisation is often decomposed into two different stages: lexical choice, which occurs during content determination, where the lexical term chosen, which may still be underspecified, is dependent on reasoning procedures, the knowledge base contents, and grammatical constraints; and lexical variation which is the choice of a particular word or form among possible synonyms or paraphrases.</Paragraph>
    <Paragraph position="4"> Lexical variation occurs in the surface realizer, and may have some pragmatic connotations, for example an implicit evaluation via the language level chosen (e.g. argotic entails low evaluation).</Paragraph>
    <Paragraph position="5"> In this project note, we show the different facets of lexicalisation in advanced QA, where the two stages, lexical choice and variation, play crucial and very distinct roles in the different parts of the response. Our model is based on a detailed analysis of QA pairs, and on annotation tasks, from which a model emerged, suitable for NLG.</Paragraph>
  </Section>
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