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 exposed to the risk of potential credit losses from an unanticipated increase in borrower defaults as well as general credit spread widening on any non-agency assets in our portfolio. We seek to manage this risk through our Manager’s pre-acquisition due diligence process and, if available, through the use of non-recourse financing, which limits our exposure to credit losses to the specific pool of collateral which is the subject of the non-recourse financing. Our Manager’s pre-acquisition due diligence process includes the evaluation of, among other things, relative valuation, supply and demand trends, the shape of various yield curves, prepayment rates, delinquency and default rates, recovery of various sectors and vintage of collateral._The potential effects of sustained inflation, rising mortgage rates, the Federal Reserve's monetary policy actions, and the ongoing COVID-19 pandemic may cause an increase in credit risk of our credit sensitive assets. Any future period of payment deferrals, forbearance, delinquencies, defaults, foreclosures or losses will likely adversely affect our net interest income from residential loans and RMBS investments, the fair value of these assets, our ability to liquidate the collateral that may underlie these investments and obtain additional financing and the future profitability of our investments. Further, in the event of delinquencies, defaults and foreclosure, regulatory changes and policies designed to protect borrowers and renters may slow or prevent us from taking remediation actions._
Assistant: