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: •In connection with acquisitions or divestitures, we may become subject to liabilities. In connection with any acquisitions, we may acquire liabilities or defects such as legal claims, including but not limited to, third party liability and other tort claims; claims for breach of contract; employment-related claims; environmental, health and safety liabilities, conditions or damage; permitting, regulatory or other compliance with law issues; or tax liabilities. If we acquire any of these liabilities, and they are not adequately covered by insurance or an enforceable indemnity or similar agreement from a creditworthy counterparty, we may be responsible for significant out-of-pocket expenditures. In connection with any divestitures, we may incur liabilities for breaches of representations and warranties or failure to comply with operating covenants under any agreement for a divestiture. We may also retain exposure on financial or performance guarantees, contractual, employment, pension and severance obligations or other liabilities of the divested business and potential liabilities that may arise under law because of the disposition or the subsequent failure of an acquiror. As a result, performance by the divested businesses or other conditions outside of our control could have a material adverse effect on our business, financial condition and results of operations. In addition, we may indemnify a counterparty in a divestiture for certain liabilities of the divested business or operations subject to the divestiture transaction. These liabilities, if they materialize, could have a material adverse effect on our business, results of operations and financial condition.
Assistant: