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Entity timelines: visual analytics and named entity evolution

The constantly evolving Web reflects the evolution of society. Knowledge about entities (people, companies, political parties, etc.) evolves over time. Facts add up (e.g., awards, lawsuits, divorces), change (e.g., spouses, CEOs, political positions), and even cease to exist (e.g., countries split into smaller or join into bigger ones). Analytics of the evolution of the entities poses many challenges including extraction, disambiguation, and canonization of entities from large text collections as well as introduction of specific analysis and interactivity methods for the evolving entity data.
 In this demonstration proposal, we consider a novel problem of the evolution of named entities. To this end, we have extracted, disambiguated, canonicalized, and connected named entities with the YAGO ontology. To analyze the evolution we have developed a visual analytics system. Careful preprocessing and ranking of the ontological data allowed us to propose wide range of effective interactions and data analysis techniques including advanced filtering, contrasting timeliness of entities and drill down/roll up evolving data.