Abstract
Relation entity extraction is an important research topic in the field of information extraction. The paper proposes an entity relation extraction model based on dependency parsing neural network, in which the dependency relations between sentences are analyzed via dependency parsing, and reveal the syntactic structure of the sentence. Experiments on several data sets show that the proposed model can improves the accuracy by 15% compared with the other method for the Chinese entity relation extraction.
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Acknowledgments
This research is supported by 2017CFB326 grants from Natural Science Foundation of Science and Technology Department of the Hubei Province.
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Cao, G., Chen, J., Yang, F., Li, C., Zhang, J. (2020). Research of Entity Relation Extraction Model Based on Dependency Parsing Neural Network. In: Liu, Y., Wang, L., Zhao, L., Yu, Z. (eds) Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. ICNC-FSKD 2019. Advances in Intelligent Systems and Computing, vol 1075. Springer, Cham. https://doi.org/10.1007/978-3-030-32591-6_39
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DOI: https://doi.org/10.1007/978-3-030-32591-6_39
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