This paper reports on an ongoing development of a tool for extracting structured information on events a given target entity participated in from massive collections of textual documents and anchoring these events on a timescale. An overview of the current version of the tool and the underlying timeline extraction process is given. Some evaluation figures that reflect system output quality are provided too. The paper will be accompanied by a live demo of the timeline extraction tool.

An ever-growing amount of information relevant for early detection of certain threats can be extracted from on-line news. This led to an emergence of news mining tools to help analysts to digest the overflow of information and to extract valuable knowledge from on line news sources. This paper gives an overview of the fully operational Real-time News Event Extraction Framework developed for Frontex, the EU Border Agency, to facilitate the process of extracting structured information on border security-related events from on-line news. In particular, a hybrid event extraction system has been constructed, which is applied to the stream of news articles continuously gathered and pre-processed by the Europe Media Monitor - a large-scale multilingual news aggregation engine. The framework consists also of an earth browser, in which events are visualized and an event moderation tool, which allows to access the database of automatically extracted event descriptions and to clean, validate, group, enhance and export them into other knowledge repositories.

OSINT (Open-Source Intelligence) tool is constructed for Frontex to automate the process of extracting structured knowledge from on-line news articles on border-security related event at the EU borders and in the related third countries. Incidents and developments are relevant context for illegal migration. European Commission has identified and acknowledged the need for strengthening capabilities for tracking the security situation.

This paper presents a near real-time multilingual news monitoring and analysis system that forms the backbone of our research work. The system integrates technologies to address the problems related to information extraction and analysis of open source intelligence on the World Wide Web. By chaining together different techniques in text mining, automated machine learning and statistical analysis, we can automatically determine who, where and, to a certain extent, what is being reported in news articles.