Towards a general theory of action and time
Artificial Intelligence
Maintaining knowledge about temporal intervals
Communications of the ACM
Guidelines for annotating temporal information
HLT '01 Proceedings of the first international conference on Human language technology research
Event ordering using TERSEO system
Data & Knowledge Engineering - Special issue: Application of natural language to information systems (NLDB04)
Splitting complex temporal questions for question answering systems
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Automating temporal annotation with TARSQI
ACLdemo '05 Proceedings of the ACL 2005 on Interactive poster and demonstration sessions
Annotating temporal information: from theory to practice
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Information Sciences: an International Journal
CU-TMP: temporal relation classification using syntactic and semantic features
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
The stages of event extraction
ARTE '06 Proceedings of the Workshop on Annotating and Reasoning about Time and Events
Automatic time expression labeling for english and chinese text
CICLing'05 Proceedings of the 6th international conference on Computational Linguistics and Intelligent Text Processing
Time for More Languages: Temporal Tagging of Arabic, Italian, Spanish, and Vietnamese
ACM Transactions on Asian Language Information Processing (TALIP)
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Until recently, most systems performing temporal extraction and reasoning from text have focused on recognizing and normalizing temporal expressions alone, for which the TIDES annotation scheme has been adopted. Temporal awareness of a text, however, involves not only identifying the temporal expressions, but the events which these expressions anchor, as well as other events which must be ordered relative to them. Because of these broader concerns, TimeML has been developed as an annotation specification that encompasses not only temporal expressions, but all temporally relevant aspects of a text. The annotation schemes, however, are not interchangeable, resulting in incompatible corpora and accompanying extraction algorithms for each standard. In this paper, we describe an automatic migration process from the TIMEX2 tags of TIDES to the TIMEX3 tags of TimeML. This transformation procedure has been implemented and evaluated with two different corpora, obtaining 93.3 and 89.2% overall F-Measure respectively.