The CoNLL-2010 Shared Task was dedicated to the detection of uncertainty cues and their linguistic scope in natural language texts. The motivation behind this task was that distinguishing factual and uncertain information in texts is of essential importance in information extraction. This paper provides a general overview of the shared task, including the annotation protocols of the training and evaluation datasets, the exact task definitions, the evaluation metrics employed and the overall results. The paper concludes with an analysis of the prominent approaches and an overview of the systems submitted to the shared task.
REF focus on the detection of uncertainty cues and their linguistic scope in natural language texts.
The CoNLL-2010 Shared Task: Learning to Detect Hedges and their Scope in Natural Language Text
Proceedings of the Fourteenth Conference on Computational Natural Language Learning
Computer Science