Abstract
In this paper, we present R-OpenIE, a rule based open information extraction method using cascaded finite-state transducer. R-OpenIE defines contextual constraint declarative rules to generate relation extraction templates, which frees from the influence of syntactic parser errors, and it uses cascaded finite-state transducer model to match the satisfied relational tuples. It is noted that R-OpenIE creates inverted index for each matched state during the matching process of cascaded finite-state transducer, which improves the efficiency of pattern matching. The experimental results have shown that our R-OpenIE can achieve good adaptability and efficiency for open information extraction.
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Acknowledgments
This work is supported by National HeGaoJi Key Project of China (No. 2013ZX01039-002-001-001), National Natural Science Foundation of China (No. 61303056, 61402464, 61502478, 61572469).
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Lin, H., Wang, Y., Zhang, P., Wang, W., Yue, Y., Lin, Z. (2016). A Rule Based Open Information Extraction Method Using Cascaded Finite-State Transducer. In: Bailey, J., Khan, L., Washio, T., Dobbie, G., Huang, J., Wang, R. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2016. Lecture Notes in Computer Science(), vol 9652. Springer, Cham. https://doi.org/10.1007/978-3-319-31750-2_26
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DOI: https://doi.org/10.1007/978-3-319-31750-2_26
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