Extending Knowledge and Deepening Linguistic Processing for the Question Answering System InSicht

  • Sven Hartrumpf
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4022)


The German question answering (QA) system InSicht participated in QA@CLEF for the second time. It relies on complete sentence parsing, inferences, and semantic representation matching. This year, the system was improved in two main directions. First, the background knowledge was extended by large semantic networks and large rule sets. Second, linguistic processing was deepened by treating a phenomenon that appears prominently on the level of text semantics: coreference resolution. A new source of lexico-semantic relations and equivalence rules has been established based on compound analyses from document parses. These analyses were used in three ways: to project lexico-semantic relations from compound parts to compounds, to establish a subordination hierarchy for compounds, and to derive equivalence rules between nominal compounds and their analytic counterparts. The lack of coreference resolution in InSicht was one major source of missing answers in QA@CLEF 2004. Therefore the coreference resolution module CORUDIS was integrated into the parsing during document processing. The central step in the QA system InSicht, matching semantic networks derived from the question parse (one by one) with document sentence networks, was generalized. Now, a question network can be split at certain semantic relations (e.g. relations for local or temporal specifications). To evaluate the different extensions, the QA system was run on all 400 German questions from QA@CLEF 2004 and 2005 with varying setups. Some extensions showed positive effects, but currently they are minor and not statistically significant. The paper ends with a discussion why improvements are not larger, yet.


Semantic Network Query Expansion Question Answering Document Processing Equivalence Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Sven Hartrumpf
    • 1
  1. 1.Intelligent Information and Communication Systems (IICS)University of Hagen (FernUniversität in Hagen)HagenGermany

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