Searching News Articles Using an Event Knowledge Graph Leveraged by Wikidata

TL;DR

This paper introduces a semantic search engine for news articles that leverages Wikidata to produce annotations and enable structured data filtering, improving fact retrieval and contextual understanding.

Contribution

It presents a novel method combining Wikidata-based semantic annotations with a search engine supporting keyword and structured data queries for news articles.

Findings

Enhanced search accuracy for news facts

Automatic inference of event schemas

Supports both keyword and structured data search

Abstract

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.