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利用自然語言處理技術,對電商客戶諮詢與投訴工單進行語義分析與意圖識別,實現自動分類與優先級排序,提升客服響應效率與用戶滿意度。
複製
Analyze the provided e-commerce customer ticket text to identify its core intent, such as logistics inquiry, return or exchange request, product quality complaint, or price consultation. Classify the ticket into the corresponding customer service queue based on predefined business rules. Simultaneously, assess the urgency of the ticket; if it involves safety complaints or significant public opinion risks, mark it as high priority and recommend immediate manual intervention. For routine inquiries, extract key entities (e.g., order number, product SKU, problem description) and generate a concise summary to help customer service agents quickly understand the context. The final output should include the classification label, priority level, list of key entities, and a summary of no more than 50 words, ensuring accuracy and facilitating subsequent processing.
複製
請分析提供的電商客戶工單文本,識別其核心意圖(如物流查詢、退換貨申請、產品質量投訴或價格諮詢),並根據預設的業務規則將其歸類至對應的客服處理隊列。同時,請評估工單的緊急程度,若涉及安全投訴或重大輿情風險,請標記為高優先級並建議立即人工介入;對於常規諮詢,請提取關鍵實體(如訂單號、商品SKU、問題描述)並生成簡潔的摘要,以便客服人員快速理解上下文。最終輸出應包含分類標籤、優先級等級、關鍵實體列表及一段不超過50字的工單摘要,確保信息準確且便於後續處理。
複製
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