Building and Displaying Name Relations using Automatic Unsupervised Analysis of Newspaper Articles
We present a tool that, from automatically recognised names, tries to infer inter-person relations in order to present associated people on maps. Based on an in-house Named Entity Recognition tool, applied on clusters of an average of 15,000 news articles per day, in 15 different languages, we build a knowledge base that allows extracting statistical co-occurrences of persons and visualising them on a per-person page or in various graphs.
POULIQUEN Bruno;
STEINBERGER Ralf;
IGNAT Camelia;
OELLINGER Tamara;
2006-11-27
JRC32545
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