Abstract
Semantic Parsing is a key problem for many artificial intelligence tasks, such as information retrieval, question answering and dialogue system. In this paper, we give the overview of the open domain semantic parsing shared task in NLPCC 2019. We first review existing semantic parsing datasets. Then, we describe open domain semantic parsing shared task in this year’s NLPCC, especially focusing on the dataset construction. The evaluation results of submissions from participating teams are presented in the experimental part.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Hemphill, C.T., Godfrey, J.J., Doddington, G.R.: The ATIS spoken language systems pilot corpus. In: Speech and Natural Language: Proceedings of a Workshop Held at Hidden Valley, Pennsylvania, 24–27 June 1990
Tang, L.R., Mooney, R.J.: Using multiple clause constructors in inductive logic programming for semantic parsing. In: Machine Learning: EMCL 2001, Proceedings of the 12th European Conference on Machine Learning, Freiburg, 5–7 September 2001, pp. 466–477 (2001)
Zelle, J.M., Mooney, R.J.: Learning to parse database queries using inductive logic programming. In: Proceedings of the Thirteenth National Conference on Artificial Intelligence and Eighth Innovative Applications of Artificial Intelligence Conference, AAAI 1996, IAAI 1996, Portland, 4–8 August 1996, vol. 2, pp. 1050–1055 (1996)
Cai, Q., Yates, A.: Large-scale semantic parsing via schema matching and lexicon extension. In: Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics, ACL 2013, 4–9 August 2013, Sofia, Volume 1: Long Papers, pp. 423–433 (2013)
Berant, J., Chou, A., Frostig, R., Liang, P.: Semantic parsing on freebase from question-answer pairs. In: Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, EMNLP 2013, 18–21 October 2013, Grand Hyatt Seattle, A meeting of SIGDAT, a Special Interest Group of the ACL, pp. 1533–1544 (2013)
Bordes, A., Usunier, N., Chopra, S., Weston, J.: Large-scale simple question answering with memory networks. CoRR, abs/1506.02075 (2015)
Trivedi, P., Maheshwari, G., Dubey, M., Lehmann, J.: LC-QuAD: a corpus for complex question answering over knowledge graphs. In: The Semantic Web - ISWC 2017 - Proceedings of the 16th International Semantic Web Conference, Part II, Vienna, 21–25 October 2017, pp. 210–218 (2017)
Talmor, A., Berant, J.: The web as a knowledge-base for answering complex questions. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2018, New Orleans, 1–6 June 2018, vol. 1 (Long Papers), pp. 641–651 (2018)
Yih, W.-t., Richardson, M., Meek, C., Chang, M.-W., Suh, J.: The value of semantic parse labeling for knowledge base question answering. In: Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016, 7–12 August 2016, Berlin, Volume 2: Short Papers (2016)
Zhong, V., Xiong, C., Socher, R.: Seq2SQL: generating structured queries from natural language using reinforcement learning. CoRR, abs/1709.00103 (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Duan, N. (2019). Overview of the NLPCC 2019 Shared Task: Open Domain Semantic Parsing. In: Tang, J., Kan, MY., Zhao, D., Li, S., Zan, H. (eds) Natural Language Processing and Chinese Computing. NLPCC 2019. Lecture Notes in Computer Science(), vol 11839. Springer, Cham. https://doi.org/10.1007/978-3-030-32236-6_74
Download citation
DOI: https://doi.org/10.1007/978-3-030-32236-6_74
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-32235-9
Online ISBN: 978-3-030-32236-6
eBook Packages: Computer ScienceComputer Science (R0)