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<Paper uid="H05-1039">
  <Title>Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing (HLT/EMNLP), pages 307-314, Vancouver, October 2005. c(c)2005 Association for Computational Linguistics Combining Deep Linguistics Analysis and Surface Pattern Learning: A Hybrid Approach to Chinese Definitional Question Answering</Title>
  <Section position="6" start_page="312" end_page="313" type="relat">
    <SectionTitle>
5 Related Work
</SectionTitle>
    <Paragraph position="0"> Ravichandran and Hovy (2002) presents a method that learns patterns from online data using some seed questions and answer anchors. The advantage is that it does not require human annotation. However, it only works for certain types of questions that  have fixed anchors, such as &amp;quot;where was X born&amp;quot;. For general definitional questions, we do not know what the anchors should be. Thus we prefer using small amounts of human annotation to derive patterns. Cui et al. (2004) uses a similar approach for unsupervised pattern learning and generalization to soft pattern matching. However, the method is actually used for sentence selection rather than answer snippet selection. Combining information extraction with surface patterns has also seen some success. Jikoun et al. (2004) shows that information extraction can help improve the recall of a pattern based system. Xu et al. (2004) also shows that manually constructed patterns are very important in answering English definitional questions. Hildebrandt et al. (2004) uses manual surface patterns for target extraction to augment database and dictionary lookup. Blair-Goldensohn et al. (2004) apply supervised learning for definitional predicates and then apply summarization methods for question answering. null</Paragraph>
  </Section>
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