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 are, and may in the future be, a party to a variety of legal actions that may affect our business, such as administrative charges before government agencies, employment and employment discrimination-related suits, employee benefit claims, breach of contract actions, tort claims and intellectual property-related litigation. In addition, because of the nature of our business, we are subject to a variety of legal actions relating to our business operations, including the design, administration and offering of our products and services. These could include claims relating to the denial or limitation of health benefits; federal and state false claims act laws; dispensing of drugs associated with our PBM business; professional liability claims arising out of the delivery of healthcare and related services to the public; development or application of medical policies and coverage and clinical guidelines; medical malpractice actions; allegations of anti-competitive and unfair business activities; provider disputes over reimbursement and contracts; provider tiering programs; narrow networks; termination of provider contracts; the recovery of overpayments from providers; fee-based business; disputes over co-payment calculations; reimbursement of out-of-network claims; the failure to disclose certain business practices; the failure to comply with various state or federal laws, including but not limited to, ERISA and the Mental Health Parity Act; and customer audits and contract performance, including government contracts. These actions or proceedings could result in substantial costs to us, require management to spend substantial time focused on litigation, result in negative media attention, and may adversely affect our business, reputation, financial condition, results of operations and cash flows.
Assistant: