TETI: a TimeML compliant TimEx tagger for Italian

In this paper we will present an ongoing research on the development of a temporal expression tagger and normalizer for Italian, compliant with the TimeML specifications. Similarly to other existing temporal expression taggers, the system is rule-based and benefits from an extensive corpus study to identify the reserved time words. However, it differs from other systems since it implements WordNet-based semantic relations between temporal expressions in order to improve its accuracy. So far, the system reports an F-measure of 86.41% for the subtask of temporal expression detection and bracketing.