Here we introduce ReTraCk (Retriever-Transducer-Checker), a neural semantic parsing framework for large scale knowledge base question answering (KBQA). ReTraCk is designed as a modular framework to achieve high flexibility and efficiency. The system includes a retriever to access relevant KB items efficiently, a transducer to generate logical form with syntax correctness guarantees, and a checker to improve the transduction procedure.
ReTraCk is ranked at top1 overall performance on the GrailQA leaderboard (as of Apr/2021) and obtains highly competitive performance on the classic WebQuestions Semantic Parse benchmark. Users can interact with the system in a timely interactive manner, further demonstrating the efficiency of the proposed framework.
Source code and Data for a system demo at ACL 2021 are available on GitHub. Contributions and collaboration are very welcome!
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