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: Mortgage loans have the potential to face heightened delinquency and default risk depending on economic conditions which could have a negative impact on the performance of the underlying collateral, resulting in declining values and an adverse impact on the obligors of such instruments. An increase in the default rate of our mortgage loan investments could have an adverse effect on our business, financial condition, results of operations and cash flows. In addition, the carrying value of mortgage loans is negatively impacted by such factors. The carrying value of our mortgage loans is stated as outstanding principal adjusted for net deferred fees and costs and unamortized discounts and premiums, less any loan loss allowances recognized. Considerations in determining allowances include, but are not limited to, the following: (i) declining debt service coverage ratios and increasing loan to value ratios; (ii) loan performance, including delinquency rates; (iii) bankruptcy filings of the borrower or major tenants or affiliates of the borrower on the property; (iv) catastrophic events at the property; (v) probability of default and recovery rate assumptions on our residential and agricultural loan portfolios; and (vi) other subjective events or factors, including economic outlook, and whether the terms of the debt will be restructured. There can be no assurance that management's assessment of loan loss allowances on mortgage loans will not change in future periods, which could lead to investment losses.
Assistant: