VisKoP: Visual Knowledge oriented Programming for Interactive Knowledge Base Question Answering
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Abstract (arXiv)
We present Visual Knowledge oriented Programming platform (VisKoP), a knowledge base question answering (KBQA) system that integrates human into the loop to edit and debug the knowledge base (KB) queries. VisKoP not only provides a neural program induction module, which converts natural language questions into knowledge oriented program language (KoPL), but also maps KoPL programs into graphical elements. KoPL programs can be edited with simple graphical operators, such as dragging to add knowledge operators and slot filling to designate operator arguments. Moreover, VisKoP provides auto-completion for its knowledge base schema and users can easily debug the KoPL program by checking its intermediate results. To facilitate the practical KBQA on a million-entity-level KB, we design a highly efficient KoPL execution engine for the back-end. Experiment results show that VisKoP is highly efficient and user interaction can fix a large portion of wrong KoPL programs to acquire the correct answer. The VisKoP online demo https://demoviskop.xlore.cn (Stable release of this paper) and https://viskop.xlore.cn (Beta release with new features), highly efficient KoPL engine https://pypi.org/project/kopl-engine, and screencast video https://youtu.be/zAbJtxFPTXo are now publicly available.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 19 of its 31 references that are in the map. First posted on arXiv 6 Jul 2023.
Builds on
19 of 31 references.
References · 19
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7 more
- 2021Leveraging Language to Learn Program Abstractions and Search Heuristicscited by 45
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- 2021Program Transfer for Answering Complex Questions over Knowledge Basescited by 34
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2 papers.