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This paper introduces a general question answering (QA) framework for Chinese domain knowledge graphs to serve various industries. The question is analyzed by shielding invalid characters in this framework, and the TransE calculation of entities and relations is used to search answer, rather than traditional logical queries that rely heavily on predefined rules. In this way, the QA framework can be easily applied to different fields with little manual participation, and reduce the migration cost caused by the lack of scalability of the existing QA systems, which are designed only for specific domains. Then, the proposed framework is operated on the space launch knowledge graph and has achieved HITS@1, HITS@3, HITS@5 scores of 60.60%, 80.87%, 85.61% separately, which is competitive with other restricted domain knowledge graphs. In addition, numerical results on the knowledge graph of the Three Kingdoms and the COVID-19-Character verified the scalability of the QA framework.

A General Framework for Chinese Domain Knowledge Graph Question Answering Based on TransE