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 and results of operations are sensitive to changes in overall economic conditions that impact customer shipping volumes, industry freight demand, industry truck capacity, inflation, and our operating costs. Regarding our operating costs, inflationary pressures persist but are generally expected to decline in the U.S. in the near-term due to easing of supply chain constraints. We cannot predict future economic conditions, fuel price fluctuations, transportation equipment resale values, or how consumer confidence could be affected by such conditions. Economic conditions that decrease shipping demand, including but not limited to public health crises, outbreaks of infectious diseases, or increases in truck capacity in the North American transportation and logistics industry, can exert downward pressure on rates and equipment utilization. In general, significant decreases in shipping volumes within the industry or increases in available truck capacity result in more aggressive freight pricing as carriers compete for loads and to maintain truck productivity. Likewise, we are also subject to cost increases outside our control that could materially reduce our profitability if we are unable to offset such increases through rate increases or cost reductions. Such cost increases include, but are not limited to, driver wages, third-party carrier costs, fuel and energy prices, taxes and interest rates, tolls, license and registration fees, insurance premiums, regulations, transportation equipment and related maintenance costs, and healthcare and other employee benefit costs. We cannot predict whether, or in what form, any such cost increases could occur. Any such cost increase or event could adversely affect our results of operations or cash flows.
Assistant: