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<Paper uid="P06-1008">
  <Title>Acceptability Prediction by Means of Grammaticality Quantification</Title>
  <Section position="8" start_page="63" end_page="63" type="concl">
    <SectionTitle>
7 Conclusion
</SectionTitle>
    <Paragraph position="0"> The method described in this paper makes it possible to give a quantified indication of sentence grammaticality. This approach is direct and takes advantage of a constraint-based representation of syntactic information, making it possible to representpreciselythesyntacticcharacteristicsofanin- null put in terms of satisfied and (if any) violated constraints. The notion of grammaticality index we have proposed here integrates different kind of information: the quality of the description (in terms of well-formedness degree), the density of information (the quantity of constraints describing an element) as well as the structure itself. These three parameters are the basic indicators of the grammaticality index.</Paragraph>
    <Paragraph position="1"> The relevance of this method has been experimentally shown, and the results described in this paper illustrate the correlation existing between the prediction (automatically calculated) expressed in terms of GI and the acceptability judgment given by subjects.</Paragraph>
    <Paragraph position="2"> This approach also presents a practical interest: it can be directly implemented into a parser. The next step of our work will be its validation on large corpora. Our parser will associate a grammatical index to each sentence. This information will be validated by means of acceptability judgments acquired on the basis of a sparse sampling strategy.</Paragraph>
  </Section>
class="xml-element"></Paper>