Abstract
For the task of open domain Knowledge Base Question Answering (KBQA) in CCKS 2021, we propose an integrated method, which complementarily combines a more generalized information retrieval model and a more accurate semantic parsing model without manual involvement of templates. Our method achieves the averaged F1-score of 78.52% on the final test data, and ranks third in the KBQA task of CCKS 2021.
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Zhen, S., Yi, X., Lin, Z., Xiao, W., Su, H., Liu, Y. (2022). An Integrated Method of Semantic Parsing and Information Retrieval for Knowledge Base Question Answering. In: Qin, B., Wang, H., Liu, M., Zhang, J. (eds) CCKS 2021 - Evaluation Track. CCKS 2021. Communications in Computer and Information Science, vol 1553. Springer, Singapore. https://doi.org/10.1007/978-981-19-0713-5_6
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DOI: https://doi.org/10.1007/978-981-19-0713-5_6
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