NAMER: A Node-Based Multitasking Framework for Multi-Hop Knowledge Base Question Answering

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 with such strategy is also published to promote further research. An online demo of NAMER is provided to visualize our framework and supply extra information for users, a video illustration of NAMER is also available.