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 growth strategy depends on our and our franchisees’ ability to open new restaurants and to operate them on a profitable basis. We expect substantially all of our international unit growth and much of our domestic unit growth to be franchised units. Accordingly, our profitability increasingly depends upon royalty revenues from franchisees. If our franchisees are not able to operate their businesses successfully under our franchised business model, our results could suffer. Additionally, we may fail to attract new qualified franchisees or existing franchisees may close underperforming locations. Planned growth targets and the ability to operate new and existing restaurants profitably are affected by economic, regulatory and competitive conditions and consumer buying habits. A decrease in sales, such as what we experienced in 2018 and the first half of 2019, or increased commodity or operating costs, including, but not limited to, employee compensation and benefits or insurance costs, could slow the rate of new store openings or increase the number of store closings. Our business is susceptible to adverse changes in local, national and global economic conditions, which could make it difficult for us to meet our growth targets. Additionally, we or our franchisees may face challenges securing financing, finding suitable store locations at acceptable terms or securing required domestic or foreign government permits and approvals. Declines in comparable sales, net store openings and related operating profits can impact our stock price. If we do not continue to improve future sales and operating results and meet our related growth targets or external expectations for net restaurant openings or our other strategic objectives in the future, our stock price could decline.
Assistant: