RICH-CPL: Fact Extraction from Wikipedia-sized Corpora for Morphologically Rich Languages
Sergei Budkov, Kseniya Buraya, Andrey A. Filchenkov, Ivan Smetannikov, Antonina Puchkovskaia · 2018
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.