Customizing GermaNet for the Use in Deep Linguistic Processing

نویسندگان

  • Melanie Siegel
  • Feiyu Xu
چکیده

In this paper we show an approach to the customization of GermaNet to the German HPSG grammar lexicon developed in the Verbmobil project. GermaNet has a broad coverage of the German base vocabulary and fine grained semantic classification, while the HPSG grammar lexicon is comparatively small und has a coarse-grained semantic classification. In our approach, we have developed a mapping algorithm to relate the synsets in GermaNet with the semantic sorts in HPSG. The evaluation result shows that this approach is useful for the lexical extension of our deep grammar development to cope with real-world text understanding. Customizing GermaNet for the Use in Deep Linguistic Processing

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تاریخ انتشار 2001