CATENA: CAusal and TEmporal relation extraction from NAtural language texts

COLING 2016 Paramita MirzaSara Tonelli

We present CATENA, a sieve-based system to perform temporal and causal relation extraction and classification from English texts, exploiting the interaction between the temporal and the causal model. We evaluate the performance of each sieve, showing that the rule-based, the machine-learned and the reasoning components all contribute to achieving state-of-the-art performance on TempEval-3 and TimeBank-Dense data... (read more)

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Evaluation results from the paper

Task Dataset Model Metric name Metric value Global rank Compare
Temporal Information Extraction TimeBank Catena F1 score 0.511 # 1