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: The value of our assets may be affected by prepayment rates on loans. As of December 31, 2023, based on unpaid principal balance, over 50% of our loans were open to repayment by the borrower without penalty. In periods of declining interest rates, prepayment rates on loans will generally increase. If interest rates decline at the same time as prepayment rates, the proceeds of such prepayments received during such periods are likely to be reinvested by us in assets yielding less than the yields on the assets that were prepaid. In periods of increasing or generally high interest rates and/or credit spreads, prepayment rates on loans will generally decrease, which could impact our liquidity, or increase our potential exposure to loan non-performance. In addition, if we originate or acquire mortgage-related securities or a pool of mortgage securities, we anticipate that the underlying mortgages will prepay at a projected rate generating an expected yield. If we purchase assets at a premium to par value, when borrowers prepay their loans faster than expected, the corresponding prepayments on the asset may reduce the expected yield on such securities because we will have to amortize the related premium on an accelerated basis. Conversely, if we purchase assets at a discount to par value, when borrowers prepay their loans slower than expected, the decrease in corresponding prepayments on the asset may reduce the expected yield on such securities because we will not be able to accrete the related discount as quickly as originally anticipated. In addition, as a result of the risk of prepayment, the market value of the prepaid assets may benefit less than other fixed income securities from declining interest rates.
Assistant: