Relation Extraction for Monitoring Economic Networks

  • Martin Had
  • Felix Jungermann
  • Katharina Morik
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5723)


Relation extraction from texts is a research topic since the message understanding conferences. Most investigations dealt with English texts. However, the heuristics found for these do not perform well when applied to a language with free word order, as is, e.g., German. In this paper, we present a German annotated corpus for relation extraction. We have implemented the state of the art methods of relation extraction using kernel methods and evaluate them on this corpus. The poor results led to a feature set which focusses on all words of the sentence and a tree kernel which includes words, in addition to the syntactic structure. The relation extraction is applied to monitoring a graph of economic company-directors network.


Production Rule Linear Kernel Parse Tree Convolution Kernel Relation Extraction 
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 2010

Authors and Affiliations

  • Martin Had
    • 1
  • Felix Jungermann
    • 1
  • Katharina Morik
    • 1
  1. 1.Department of Computer Science - Artificial Intelligence GroupTechnical University of DortmundDortmundGermany

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