This paper describes the system SPINOZA.VU developed for the SemEval 2015 Task 4: Cross Document TimeLines. The system integrates output from the News-Reader Natural Language Processing pipeline and is designed following an entity based model. The poor performance of the submitted runs are mainly a consequence of error propagation. Nevertheless, the error analysis has shown that the interpretation module behind the system performs correctly. An out of competition version of the system has fixed some errors and obtained competitive results. Therefore, we consider the system an important step towards a more complex task such as storyline extraction.
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