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 regularly monitor the recoverability of our long-lived assets, such as buildings and improvements and machinery and equipment, and evaluate their carrying value for potential impairment, whenever events or changes in circumstances indicate that the carrying amount of such assets may not be fully recoverable. We review goodwill on an annual basis to determine if impairment has occurred and review the recoverability of fixed assets and intangible assets, generally on a quarterly basis and whenever events or changes in circumstances indicate that impairment may have occurred or the value of such assets may not be fully recoverable. Examples of indicators of potential impairment of our long-lived assets may include a significant decrease in the market price, an adverse change in how a property is being used, an accumulation of costs significantly in excess of the amount originally expected for the acquisition or development, a change in our intended holding period due to our intention to sell an asset, a history of operating losses or a material decline in profitability (of a property or a reporting unit). If such reviews indicate that impairment has occurred, we are required to record a non-cash impairment charge for the difference between the carrying value and fair value of the long-lived assets in the period the determination is made. The testing of long-lived assets and goodwill for impairment requires the use of estimates based on significant assumptions about our future revenue, profitability, cash flows, fair value of assets and liabilities, weighted average cost of capital, as well as other assumptions. Changes in these estimates, or changes in actual performance compared with these estimates, may affect the fair value of long-lived assets, which could result in an impairment charge.
Assistant: