We present an approach for detecting salient (important) dates in texts in order to auto- matically build event timelines from a search query (e.g. the name of an event or person, etc.). This work was carried out on a corpus of newswire texts in English provided by the Agence France Presse (AFP). In order to ex- tract salient dates that warrant inclusion in an event timeline, we first recognize and normal- ize temporal expressions in texts and then use a machine-learning approach to extract salient dates that relate to a particular topic. We fo- cused only on extracting the dates and not the events to which they are related.

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