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<Paper uid="W97-0310">
  <Title>Assigning Grammatical Relations with a Back-off Model</Title>
  <Section position="8" start_page="647" end_page="647" type="concl">
    <SectionTitle>
5 Conclusion
</SectionTitle>
    <Paragraph position="0"> This paper describes a procedure to automatically assign grammatical subject/object relations to ambiguous German constructs. It is based on an unsupervised learning procedure to collect test and training data and the back-off model to make assignment decisions. The system was implemented and tested on a 15-million word newspaper corpus.</Paragraph>
    <Paragraph position="1"> The overall accuracy of the decision algorithm was almost 3% higher than the baseline of 87.83% established. The accuracy of the procedure for tuples for which a decision was made based on training pairs/triples (P2 and P3) exceeded 95%.</Paragraph>
    <Paragraph position="2"> In order to increase the coverage for these cases as well as the overall performance of the procedure, the sample space should be reduced by morphologically processing German compound nouns, and the size of the training set should be increased. Further, in the experiment described in this paper, the model was trained with data obtained by an unsupervised procedure which performs with an accuracy of approximately 87% for training data. Further development of the morphology component and grammar definition should lead to improved results.</Paragraph>
  </Section>
class="xml-element"></Paper>