S. Budkov, Kseniya Buraya, A. Filchenkov, I. Smetannikov, A. Puchkovskaia
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RICH-CPL: Fact Extraction from Wikipedia-sized Corpora for Morphologically Rich Languages
This work deals with never-ending learning approach for fact extraction from unstructured Russian text. It continues the research in the field of pattern learning techniques for morphologically rich free-word-order language. We introduce improvements for CPL-RUS algorithm and choose best initial parameters. We conducted experiments with the extended version, RICH-CPL algorithm on the corpus containing over 1.3 million pages. This paper is shortened version of our paper [7] that includes also new modifications of the proposed methods.
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