Abstract
Human languages exhibit a variety of strategies for communicating spatial information, including toponyms, spatial nominals, locations that are described in relation to other locations, and movements along paths. SpaceEval is a combined information extraction and classification task with the goal of identifying and categorizing such spatial information. In this paper, we describe the SpaceEval task, annotation schema, and corpora, and evaluate the performance of several supervised and semi-supervised machine learning systems developed with the goal of automating this task.
Cite
CITATION STYLE
Pustejovsky, J., Kordjamshidi, P., Moens, M. F., Levine, A., Dworman, S., & Yocum, Z. (2015). SemEval-2015 Task 8: SpaceEval. In SemEval 2015 - 9th International Workshop on Semantic Evaluation, co-located with the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2015 - Proceedings (pp. 884–894). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s15-2098
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