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 may pursue business opportunities that diverge from our current business model, including expanding our products or service offerings, investing in new and unproven technologies, adding customer acquisition channels, and forming new alliances with companies to market our services. We can provide no assurance that any such business opportunities will prove to be successful. Among other negative effects, our pursuit of such business opportunities could cause our cost of investment in new customers to grow at a faster rate than our recurring revenue and fees collected at the time of installation. In addition, any new business partner may not agree to the terms and conditions or limitations on liability that we typically impose upon third parties. We have acquired DataShield, LLC and Secure Designs, each of which provide cybersecurity services for business customers, which expands our suite of services. As companies are under increasing attack by cybercriminals around the world, a breach by such cybercriminals of our customers’ systems or operations could result in claims and lawsuits against us and result in damage to our brand and reputation. We have also acquired several companies that sell and service fire and integrated security systems to business customers, including Red Hawk Fire & Security, which significantly expanded our commercial fire and security capabilities, reach, and customer base. In addition, as we expand our products and services to larger commercial installations, we may have customers who experience large commercial losses that result in claims and lawsuits against us and result in damage to our brand and reputation. In January 2020, we acquired Defenders, which was our largest authorized dealer in 2019. While this acquisition expands our direct go-to-market operations, we cannot be certain that we can maintain the level of new account generation through Defenders as was achieved through Defenders prior to the acquisition or that we can maintain as effective a third-party dealer
Assistant: