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Common applications of text transformation in Natural Language Processing include machine translation, summarization, and text style transfer.

Examples of Text Transformation Tasks

Analyze the following input-output text pairs and match each pair to the specific text transformation task it represents.

A user provides the following formal text: 'Esteemed Colleagues, Please be advised that the quarterly review meeting has been rescheduled to Friday, October 27th, at 10:00 AM in Conference Room 3. Your punctual attendance is required.' Their goal is to convert this into a casual message suitable for an internal team chat. Which of the following outputs best accomplishes this specific text transformation task?

A software company has accumulated thousands of lengthy customer support chat transcripts. They want to analyze these transcripts to identify common issues and create concise, easy-to-understand entries for their public FAQ page. The raw transcripts are often over 1,000 words long and filled with conversational filler. Considering the company's goal, which text transformation application would be the most crucial to apply first, and why?

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