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 performance is subject to economic conditions and their impact on levels of spending by businesses and individuals. Most of the sellers that use our services are small businesses, many of which are in the early stages of their development, and these businesses are often disproportionately adversely affected by economic downturns and may fail at a higher rate than larger or more established businesses. In fact, small businesses have been, and continue to be, disproportionately affected by the COVID-19 pandemic and the related measures taken by governments and private industry to protect the public health such as stay-at-home orders. Many businesses are experiencing reduced sales and are processing fewer payments with us, which has had a negative impact on our results of operations. If they cease to operate, they will likely stop using our products and services altogether. Small businesses frequently have limited budgets and limited access to capital, and they may choose to allocate their spending to items other than our financial or marketing services, especially in times of economic uncertainty or in recessions. In addition, if more of our sellers cease to operate, this may have an adverse impact not only on the growth of our payments services but also on our transaction and advance loss rates, and the success of our other services. For example, if sellers processing payments with us receive chargebacks after they cease to operate, we may incur additional losses. Additionally, the growth in the number of sellers qualifying for participation in the Square Capital program may slow, or business loans may be paid more slowly, or not at all. In addition, as we expand our business to offer consumer financing products, those customers may also be disproportionately adversely affected by economic downturns.
Assistant: