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 depends on, and is directly affected by, the global automobile industry. Automotive production and sales are highly cyclical and depend on general economic conditions and other factors, including consumer spending and preferences, changes in interest rate levels and credit availability, consumer confidence, fuel costs, fuel availability, environmental impact, governmental incentives and regulatory requirements, and political volatility, especially in energy-producing countries and growth markets. Such factors may also negatively impact consumer demand for automobiles that include features such as our products. In addition, automotive production and sales can be affected by our customers’ ability to continue operating in response to challenging economic conditions, and in response to labor relations issues, regulatory requirements, trade agreements and other factors. The volume of global automotive production has fluctuated, sometimes significantly, from year to year, and such fluctuations give rise to fluctuations in the demand for our products. Moreover, the automotive industry has recently experienced, and may continue to experience, a semiconductor shortage, which has negatively impacted the production of new vehicles. Any significant adverse change in any of these factors, including, but not limited to, general economic conditions and the resulting bankruptcy of a customer, the closure of a customer manufacturing facility or the ability of a customer manufacturing facility to obtain supplies to manufacture automobiles and to ship or receive shipments of parts, supplies or finished product, may result in a reduction in automotive sales and production by our customers, and could have a material adverse effect on our business, results of operations and financial condition.
Assistant: