Two is Better Than One: Answering Complex Questions by Multiple Knowledge Sources with Generalized Links

• URL: http://arxiv.org/abs/2309.05201v1
• Date: Mon, 11 Sep 2023 02:31:41 GMT
• Title: Two is Better Than One: Answering Complex Questions by Multiple Knowledge Sources with Generalized Links
• Authors: Minhao Zhang, Yongliang Ma, Yanzeng Li, Ruoyu Zhang, Lei Zou, Ming Zhou
• Abstract summary: We formulate the novel Multi-KB-QA task that leverages the full and partial links among multiple KBs to derive correct answers. We propose a method for Multi-KB-QA that encodes all link relations in the KB embedding to score and rank candidate answers.
• Score: 31.941956320431217
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Incorporating multiple knowledge sources is proven to be beneficial for answering complex factoid questions. To utilize multiple knowledge bases (KB), previous works merge all KBs into a single graph via entity alignment and reduce the problem to question-answering (QA) over the fused KB. In reality, various link relations between KBs might be adopted in QA over multi-KBs. In addition to the identity between the alignable entities (i.e. full link), unalignable entities expressing the different aspects or types of an abstract concept may also be treated identical in a question (i.e. partial link). Hence, the KB fusion in prior works fails to represent all types of links, restricting their ability to comprehend multi-KBs for QA. In this work, we formulate the novel Multi-KB-QA task that leverages the full and partial links among multiple KBs to derive correct answers, a benchmark with diversified link and query types is also constructed to efficiently evaluate Multi-KB-QA performance. Finally, we propose a method for Multi-KB-QA that encodes all link relations in the KB embedding to score and rank candidate answers. Experiments show that our method markedly surpasses conventional KB-QA systems in Multi-KB-QA, justifying the necessity of devising this task.

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