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 compete in numerous segments of the restaurant, hotel, working spaces, well-being, digital and retail industries, each of which faces its own challenges. Although we do not believe that we have a single direct competitor across all of the different sectors and geographies in which we operate, we face direct competition from other private members’ clubs, restaurants, bars, spas, hotels and co-working spaces that exist locally in proximity to our own Houses. No assurances can be given that these competing local clubs, restaurants, accommodation, co-working spaces, well-being, digital or retail providers, or other new entrants in any of these industries, will not expand and compete with us locally or globally. We believe that these business sectors are each highly competitive and primary competitive factors include name recognition, demographic considerations, effectiveness of public relations and brand recognition, level of service, convenience of location, quality of the property, pricing, product or service and range and quality of services and amenities offered. We compete with other restaurants, boutique hotels, co-working spaces and beauty care and retailers on a local level, as well as on a global level against certain larger chains with properties in the markets in which we operate. This competition may limit our ability to attract and retain existing members and customers and our ability to attract new members and customers. If we are unable to compete effectively in any of these market sectors, we could lose market share, which could adversely affect our business, results of operation and financial condition.
Assistant: