Abstract
Word semantic relation classification is a challenging task for natural language processing, so we organize a semantic campaign on this task at NLPCC 2017. The dataset covers four kinds of semantic relations (synonym, antonym, hyponym and meronym), and there are 500 word pairs per category. Together 17 teams submit their results. In this paper, we describe the data construction and experimental setting, make an analysis on the evaluation results, and make a brief introduction to some of the participating systems.
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Acknowledgement
This work is supported by National High Technology Research and Development Program of China (2015AA015403), National Natural Science Foundation of China (61371129).
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Wu, Y., Zhang, M. (2018). Overview of the NLPCC 2017 Shared Task: Chinese Word Semantic Relation Classification. In: Huang, X., Jiang, J., Zhao, D., Feng, Y., Hong, Y. (eds) Natural Language Processing and Chinese Computing. NLPCC 2017. Lecture Notes in Computer Science(), vol 10619. Springer, Cham. https://doi.org/10.1007/978-3-319-73618-1_81
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DOI: https://doi.org/10.1007/978-3-319-73618-1_81
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