Title:
Multilingual and Domain-sensitive Temporal Tagging

Abstract:
Temporal information is of major importance in virtually all contexts, and
thus, it also occurs frequently in many types of text documents in the form of
temporal expressions. An important characteristic of temporal expressions is
that they can be normalized so that their meaning is unambiguous and can be
placed on a timeline. In many research areas in which natural language
processing is involved, e.g., in information retrieval and question answering,
applications can highly benefit from having access to normalized information
instead of only the words as they occur in documents.
In this talk, we present our work on multilingual and domain-sensitive
temporal tagging. After explaining the challenges of a temporal tagger,
strategies for successful multilingual, domain-sensitive temporal tagging are
presented as realized by our temporal tagger HeidelTime. Finally, we outline
our current work and discuss open issues.