Searching News Articles Using an Event Knowledge Graph Leveraged by Wikidata
This addresses the challenge for journalists and news agencies in efficiently finding contextual background and comparing past events, though it appears incremental as it builds on existing knowledge bases and search techniques.
The paper tackles the problem of searching for precise facts in news articles by proposing a method that uses Wikidata to create semantic annotations, and develops a semantic search engine that supports both keyword and structured data search with automatically inferred event schema filters.
News agencies produce thousands of multimedia stories describing events happening in the world that are either scheduled such as sports competitions, political summits and elections, or breaking events such as military conflicts, terrorist attacks, natural disasters, etc. When writing up those stories, journalists refer to contextual background and to compare with past similar events. However, searching for precise facts described in stories is hard. In this paper, we propose a general method that leverages the Wikidata knowledge base to produce semantic annotations of news articles. Next, we describe a semantic search engine that supports both keyword based search in news articles and structured data search providing filters for properties belonging to specific event schemas that are automatically inferred.