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<Paper uid="C02-1079">
  <Title>Best Analysis Selection in Inflectional Languages</Title>
  <Section position="5" start_page="0" end_page="0" type="concl">
    <SectionTitle>
4 Conclusions
</SectionTitle>
    <Paragraph position="0"> The methods of the best analysis selection algorithm described in this paper show that the parsing of inflectional languages calls for sensitive approaches to the evaluation of the appropriate figures of merit. The case study of Czech suggests that the use of language specific features can improve the results of simple stochastic techniques on annotated corpus data.</Paragraph>
    <Paragraph position="1"> Future directions of our research lead to improvements of the quality of training data set so that it would cover all the most frequent language phenomena. Our investigations indicate that, in addition to verbs, the best analysis selection algorithms could also take advantage of valency frames of other POS categories (nouns, adjectives).</Paragraph>
  </Section>
class="xml-element"></Paper>