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: We sell our products pursuant to agreements that are generally for annual terms. Our customers have no obligation to renew their subscriptions after their subscription period expires, and we have experienced losses of customers that elected not to renew, in some cases, for reasons beyond our control. For example, our largest customer during 2020 faced bankruptcy and, as a result, we lost substantially all of the revenue we expected to generate from this customer in 2020. In addition, even if subscriptions are renewed, they may not be renewed on the same or on more profitable terms. As a result, our ability to retain our existing customers and grow depends in part on subscription renewals. We may not be able to accurately predict future trends in customer renewals, and our customers’ renewal rates have and may continue to fluctuate because of several factors, including their satisfaction or dissatisfaction with our services, the cost of our services and the cost of services offered by our competitors, a customer’s ability to build a video streaming solution in-house, reductions in our customers’ spending levels or the introduction by competitors of attractive features and functionality. If our customer retention rate decreases, we may need to increase the rate at which we add new customers in order to maintain and grow our revenue, which may require us to incur significantly higher sales and marketing expenses than we currently anticipate, or our revenue may decline. If our customers do not renew their subscriptions for our services, renew on less favorable terms, or do not purchase additional functionality or subscriptions, our revenue may grow more slowly than expected or decline, and our profitability and gross margins may be harmed or affected.
Assistant: