@inproceedings{zhang-etal-2021-namer,
    title = "{NAMER}: A Node-Based Multitasking Framework for Multi-Hop Knowledge Base Question Answering",
    author = "Zhang, Minhao  and
      Zhang, Ruoyu  and
      Zou, Lei  and
      Lin, Yinnian  and
      Hu, Sen",
    editor = "Sil, Avi  and
      Lin, Xi Victoria",
    booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Demonstrations",
    month = jun,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2021.naacl-demos.3/",
    doi = "10.18653/v1/2021.naacl-demos.3",
    pages = "18--25",
    abstract = "We present NAMER, an open-domain Chinese knowledge base question answering system based on a novel node-based framework that better grasps the structural mapping between questions and KB queries by aligning the nodes in a query with their corresponding mentions in question. Equipped with techniques including data augmentation and multitasking, we show that the proposed framework outperforms the previous SoTA on CCKS CKBQA dataset. Moreover, we develop a novel data annotation strategy that facilitates the node-to-mention alignment, a dataset (\url{https://github.com/ridiculouz/CKBQA}) with such strategy is also published to promote further research. An online demo of NAMER (\url{http://kbqademo.gstore.cn}) is provided to visualize our framework and supply extra information for users, a video illustration (\url{https://youtu.be/yetnVye_hg4}) of NAMER is also available."
}