Knowledge is essential for understanding. The ongoing explosion of information highlights the need for electronic texts that allow machines to better understand human language. The explosion of information in various fields has greatly changed our lives. Among them, the information explosion of the film is particularly prominent. Nowadays, people's requirements for high quality of spiritual life are increasing, and people's demand for movies is also increasing. With the extensive coverage of the Internet, the amount of movie-related information is also increasing, so how to design and build a question-and-answer system about movies is more and more urgent and important. At the same time, the original intention of the knowledge graph is to express various entities, concepts that exist objectively in the real world, and various relationships between them. It can better understand the abstract components in the language, and better to confirm the information through the interaction of the ambiguous parts of the language. In addition, the upgrade of deep learning natural language processing technology allows us to better understand and analyse language. In view of the above advantages, the movie question answering system in this paper is constructed based on the knowledge graph and uses natural language processing technology.
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