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<Paper uid="C90-3016">
  <Title>Structured Meanings in Computational Linguistics</Title>
  <Section position="7" start_page="87" end_page="87" type="concl">
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4 88
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    <Paragraph position="0"> be defined on the basis of Rosetta's M-trees. iNow we will indicate briefly how M-trees can be applied to propositional attitudes and to natural language generation outside the context of automatic translation.</Paragraph>
    <Paragraph position="1"> But~ there is a caveat, discussed under the header of &amp;quot;mixed inference&amp;quot;.</Paragraph>
    <Paragraph position="2"> Propositional Attitudes. Given that meanings are M-trees, the natural solution to the problem of &amp;quot;de dicto&amp;quot; propositional attitudes is to let epistemic attitudes denote a relation between an individual and an M-tree. Consequently, if a person x knows that S, while S' and S share the same M-tree, then x is predicted to also know that S ~. Since this amounts to a much stronger relation of synonymy than logical equivalence (t-equivalence), the problems noted in the in~roduction do not arise. The general situation is that if x knows that S and S ~-M S&amp;quot;, then it is predicted that x also knows that S H.</Paragraph>
    <Paragraph position="3"> Natural Language Generation. Even outside the domain of automatic translation, M-trees can be used for naturM language generation. For example, in a natural language question-answering application, the M-tree derived from the input-question can serve as a basis for generation, after some operations on the original M-tree, in which a yes-no question is changed into an affirmative or negative answer, for instance.</Paragraph>
    <Paragraph position="4"> In most applications where there is no Mdegtree available, other means than M-trees can be used. For instance, when the user of a query system asks assistance from the computer's help facility, pre-stored natural language text can replace M-trees.</Paragraph>
    <Paragraph position="5"> Mixed Inference. We have seen that inference on the basis of M-trees is feasible, but how about inference on the basis of premises, some of which are purely logical while others are fully dressed M-trees? Two obvious approaches (where ~, denotes mixed inference, and T 4, is a variable over those M-trees having 4' corresponding to their top nodes) are  (i) C/, T p-~ C/ ~,~ C/,x t = C/ (xisthe corresponding formula of T's top node),</Paragraph>
    <Paragraph position="7"> Neither solution is satisfying: the first leaves T's linguistic structure unused; and the second, which quantifies over all the possible ways in which C/ can be expressed, is computationally intractable. The problem wi~h mixed inference illustrates the one weak side of structured meanings: they let linguistic structure contribute to the meaning of an expression, but; it is impo~sible to say (in model theoretic terms) what it contributes.</Paragraph>
  </Section>
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