Direct transitive closure algorithms: design and performance evaluation
ACM Transactions on Database Systems (TODS)
A maximum-entropy-inspired parser
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Machine Learning
NLTK: the Natural Language Toolkit
ETMTNLP '02 Proceedings of the ACL-02 Workshop on Effective tools and methodologies for teaching natural language processing and computational linguistics - Volume 1
Machine learning of temporal relations
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
CU-TMP: temporal relation classification using syntactic and semantic features
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
NAIST.Japan: temporal relation identification using dependency parsed tree
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Jointly identifying temporal relations with Markov Logic
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
Exploring the effectiveness of lexical ontologies for modeling temporal relations with Markov logic
SIGDIAL '10 Proceedings of the 11th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Aspectual type and temporal relation classification
EACL '12 Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
Towards unsupervised learning of temporal relations between events
Journal of Artificial Intelligence Research
Temporal Relation Identification and Classification in Clinical Notes
Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics
Classifying temporal relations in clinical data: A hybrid, knowledge-rich approach
Journal of Biomedical Informatics
Towards generating a patient's timeline: Extracting temporal relationships from clinical notes
Journal of Biomedical Informatics
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As a participant in TempEval-2, we address the temporal relations task consisting of four related subtasks. We take a supervised machine-learning technique using Markov Logic in combination with rich lexical relations beyond basic and syntactic features. One of our two submitted systems achieved the highest score for the Task F (66% precision), untied, and the second highest score (63% precision) for the Task C, which tied with three other systems.