  We are presenting a text analysis tool set that allows analysts in various
fields to sieve through large collections of multilingual news items quickly
and to find information that is of relevance to them. For a given document
collection, the tool set automatically clusters the texts into groups of
similar articles, extracts names of places, people and organisations, lists the
user-defined specialist terms found, links clusters and entities, and generates
hyperlinks. Through its daily news analysis operating on thousands of articles
per day, the tool also learns relationships between people and other entities.
The fully functional prototype system allows users to explore and navigate
multilingual document collections across languages and time.
