Socio-Political Event Extraction Using a Rule-Based Approach

News reports are currently one of the most studied data sources in the field of information extraction. Event descriptions that come from these sources are controversial, complementary and reflect relationships between the participating entities. The aim of the present work is to test a group of predefined patterns and rules to obtain sets of automatically filled scenario templates for socio-political events case study: protests and to apply clustering algorithms. At this stage the information is extracted from Russian news titles. The results of the pattern quality assessment and clustering are presented.

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