Complex Knowledge Base Question Answering: A Survey

Yunshi Lan, Gaole He, Jinhao Jiang, Jing Jiang, Wayne Xin Zhao, Ji Rong Wen

Research output: Contribution to journalArticleScientificpeer-review

4 Citations (Scopus)
28 Downloads (Pure)

Abstract

Knowledge base question answering (KBQA) aims to answer a question over a knowledge base (KB). Early studies mainly focused on answering simple questions over KBs and achieved great success. However, their performances on complex questions are still far from satisfactory. Therefore, in recent years, researchers propose a large number of novel methods, which looked into the challenges of answering complex questions. In this survey, we review recent advances in KBQA with the focus on solving complex questions, which usually contain multiple subjects, express compound relations, or involve numerical operations. In detail, we begin with introducing the complex KBQA task and relevant background. Then, we present two mainstream categories of methods for complex KBQA, namely semantic parsing-based (SP-based) methods and information retrieval-based (IR-based) methods. Specifically, we illustrate their procedures with flow designs and discuss their difference and similarity. Next, we summarize the challenges that these two categories of methods encounter when answering complex questions, and explicate advanced solutions as well as techniques used in existing work. After that, we discuss the potential impact of pre-trained language models (PLMs) on complex KBQA. To help readers catch up with SOTA methods, we also provide a comprehensive evaluation and resource about complex KBQA task. Finally, we conclude and discuss several promising directions related to complex KBQA for future research.

Original languageEnglish
Pages (from-to)11196 - 11215
Number of pages20
JournalIEEE Transactions on Knowledge and Data Engineering
Volume35
Issue number11
DOIs
Publication statusPublished - 2022

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • Cognition
  • Compounds
  • Knowledge base
  • knowledge base question answering
  • Knowledge based systems
  • natural language processing
  • question answering
  • Question answering (information retrieval)
  • Semantics
  • survey
  • Task analysis
  • TV

Fingerprint

Dive into the research topics of 'Complex Knowledge Base Question Answering: A Survey'. Together they form a unique fingerprint.

Cite this