Deep Query Ranking for Question Answering over Knowledge Bases
We study question answering systems over knowledge graphs which map an input natural language question into candidate formal queries. Often, a ranking mechanism is used to discern the queries with higher similarity to the given question. Considering the intrinsic complexity of the natural language, finding the most accurate formal counter-part is a challenging task. In our recent paper , we leveraged Tree-LSTM to exploit the syntactical structure of input question as well as the candidate formal queries to compute the similarities. An empirical study shows that taking the structural information of the input question and candidate query into account enhances the performance, when compared to the baseline system. Code related to this paper is available at: https://github.com/AskNowQA/SQG.
This research was supported by EU H2020 grants for the projects HOBBIT (GA no. 688227), WDAqua (GA no. 642795) as well as by German Federal Ministry of Education and Research (BMBF) for the project SOLIDE (no. 13N14456).
- 2.Diefenbach, D., Lopez, V., Singh, K., Maret, P.: Core techniques of question answering systems over knowledge bases: a survey. Knowl. Inf. Syst., pp. 1–41 (2017)Google Scholar
- 3.Bast, H., Haussmann, E.: More accurate question answering on freebase. In: Proceedings of the 24th ACM International on Conference on Information and Knowledge Management, pp. 1431–1440. ACM (2015)Google Scholar
- 4.Abujabal, A., Yahya, M., Riedewald, M., Weikum, G.: Automated template generation for question answering over knowledge graphs. In: Proceedings of the 26th International Conference on World Wide Web, pp. 1191–1200 (2017)Google Scholar
- 5.Bordes, A., Chopra, S., Weston, J.: Question answering with subgraph embeddings. arXiv preprint arXiv:1406.3676 (2014)
- 6.Yih, S.W.-T., Chang, M.-W., He, X., Gao, J.: Semantic parsing via staged query graph generation: question answering with knowledge base. In: Proceedings of the Joint Conference of ACL and AFNLP (2015)Google Scholar
- 7.Tai, K.S., Socher, R., Manning, C.D.: Improved semantic representations from tree-structured long short-term memory networks. In: ACL (2015)Google Scholar
- 8.Yih, W.-T., Richardson, M., Meek, C., Chang, M.-W.: The value of semantic parse labeling for knowledge base question answering. In: 54th Annual Meeting of the Association for Computational Linguistics, pp. 201–206 (2016)Google Scholar