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E-commerce Ticket Classification

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Leverage natural language processing to semantically analyze user-submitted after-sales inquiry and complaint tickets on e-commerce platforms. Automatically identify issue types such as logistics delays, product damage, or refund disputes, extract key entities, and provide structured data for subsequent manual intervention or automated workflows, thereby enhancing customer service response efficiency and user satisfaction.

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Analyze the following e-commerce after-sales ticket text to identify its problem category, including logistics issues, product quality issues, after-sales service attitude, or refund disputes. Extract key entities such as order numbers, product names, user requests, and sentiment tendencies. Finally, output a structured classification result and suggested handling priority to enable the customer service team to respond quickly.

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