Abstract : In this paper, we present an unsupervised
pipeline approach for clustering news articles
based on identified event instances in
their content. We leverage press agency
newswire and monolingual word alignment
techniques to build meaningful and
linguistically varied clusters of articles
from the Web in the perspective of a
broader event type detection task. We validate
our approach on a manually annotated
corpus of Web articles.
