The Logical Approach to Temporal Reasoning
Artificial Intelligence Review
Introduction to the special issue on temporal information processing
ACM Transactions on Asian Language Information Processing (TALIP) - Special Issue on Temporal Information Processing
Temporal reasoning for decision support in medicine
Artificial Intelligence in Medicine
Temporal abstraction in intelligent clinical data analysis: A survey
Artificial Intelligence in Medicine
SemEval-2007 task 15: TempEval temporal relation identification
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
An interval-based representation of temporal knowledge
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 1
SemEval-2010 task 13: TempEval-2
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
TRIPS and TRIOS system for TempEval-2: Extracting temporal information from text
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
TIPSem (English and Spanish): Evaluating CRFs and semantic roles in TempEval-2
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
MAE and MAI: lightweight annotation and adjudication tools
LAW V '11 Proceedings of the 5th Linguistic Annotation Workshop
A corpus of clinical narratives annotated with temporal information
Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium
Journal of Biomedical Informatics
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Temporal information in clinical narratives plays an important role in patients' diagnosis, treatment and prognosis. In order to represent narrative information accurately, medical natural language processing (MLP) systems need to correctly identify and interpret temporal information. To promote research in this area, the Informatics for Integrating Biology and the Bedside (i2b2) project developed a temporally annotated corpus of clinical narratives. This corpus contains 310 de-identified discharge summaries, with annotations of clinical events, temporal expressions and temporal relations. This paper describes the process followed for the development of this corpus and discusses annotation guideline development, annotation methodology, and corpus quality.