System: You are provided with a paragraph. Your goal is to automatically identify the most relevant tasks based on the content of the paragraph and generate an example of entailment (if the task conclusion can be logically inferred from the paragraph) and a different example of non-entailment (if it is unclear or the opposite conclusion is true). 

Step 1: Read the paragraph carefully. 
Step 2: Automatically decide which tasks are relevant based on the paragraph’s content. Relevant tasks may include, but are not limited to: 
    - Topic Classification 
    - Risk Classification
    - Sentiment Classification 
    - Tone Classification
    - Event Detection 
    - Entity Recognition 
    - Geographical Recognition 
    - Trend Detection 
    - Intent Detection 
    - Sector Identification 
    - Impact Classification 
    - Tense Identification (Past, Present, Future) 
    - Uncertainty Identification 

Step 3: For each relevant task you identify, generate two clear and concise examples whose labels match common practices for the task at hand: one for entailment and one for non-entailment. The example should speak about the text at the 3rd person. 
Step 4: Output the results in the following JSON format:

{
    'relevant_tasks': [
        {
            'task': <The automatically selected relevant task>,
            'examples': [
                {
                    'input': <The entailment example based on the paragraph>,
                    'label': 'entailment',
                },
                {
                    'input': <The non-entailment example (neutral or contradiction) based on the paragraph>,
                    'label': 'non-entailment',
                }
            ]
        },
        ...
    ]
}
User: Our business strategy includes the differentiation of our brand and product from the other U.S. airlines, including LCCs and ULCCs, in order to increase customer loyalty and drive future ticket sales. We intend to accomplish this by continuing to offer passengers dependable customer service. However, in the past, we have experienced customer complaints related to, among other things, product and pricing changes related to our business strategy and customer service. In particular, we have generally experienced a higher volume of complaints when we implemented changes to our unbundling policies, such as charging for seats and baggage. These complaints, together with reports of lost baggage, delayed and cancelled flights, and other service issues, are reported to the public by the DOT. In addition, we could become subject to complaints about our booking practices. Finally, we experienced a significant number of complaints, including letters from lawmakers and attorneys general, concerning non-refundable tickets during the COVID-19 pandemic. If we do not meet our customers’ expectations with respect to reliability and service, our brand and product could be negatively impacted, which could result in customers deciding not to fly with us and adversely affect our business and reputation. We have agreements for bus service to transport passengers to our MSP hub. If these operators suffer a service problem, safety failure or accident, our brand would be negatively impacted.
Assistant: