Sharonova, Natalia ValeriyevnaDoroshenko, AnastsiiaCherednichenko, Olga2020-06-012020-06-012018Sharonova N. Issues of Fact-based Information Analysis [Electronic resource] / N. Sharonova, A. Doroshenko, O. Cherednichenko // Computational linguistics and intelligent systems (COLINS 2018) : proc. of the 2nd Intern. Conf., June 25-27, 2018. Vol. 1: Main Conference / ed.: V. Lytvyn [et al.]. – Electron. text data. – Lviv, 2018. – P. 11-19. – URL: http://ceur-ws.org/Vol-2136/10000011.pdf, free (accessed 01.06.2020).https://repository.kpi.kharkov.ua/handle/KhPI-Press/46677With the recent growth of Internet, mobile and social networks the spread of fake news and click-baits increases drastically. Today, the fact retrieval system is one of the most effective tools for identifying the information for decision-making. We propose the approach based on factual information systematization. Different interpretations of the same phenomenon, as well as the inconsistency, inaccuracy or mismatch in information coming from different sources, lead to the task of factual information extraction. In this work, we explore how can natural language processing methods help to check contradictions and mismatches in facts automatically. The reference model of the factbased analytical system is proposed. It consists of such basic components as Document Search component, Fact retrieval component, Fact Analysis component, Visualization component, and Control component.enfactnatural language processinginformation extractioncomparator identificationpredicatereference modelThesis