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 majority of our lending involves transitional loans to borrowers who are typically seeking relatively short-term capital to be used in an acquisition or rehabilitation of a property. The typical borrower in a transitional loan has usually identified an asset that it views as undervalued, having been under-managed and/or located in a recovering market. If the borrower’s assessment of the asset as undervalued is inaccurate, or if the market in which the asset is located fails to improve according to the borrower’s projections, or if the borrower fails to improve the quality of the asset’s management and/or the value of the asset, the borrower may not receive a sufficient return on the asset to satisfy the transitional loan, and we bear the risk that we may not recover all or a portion of our investment. During periods in which there are decreases in demand for certain properties as a result of macroeconomic factors, reductions in the financial resources of tenants and defaults by borrowers or tenants, borrowers face additional challenges in transitioning properties. Market downturns or other adverse macroeconomic factors may affect transitional loans in our portfolio more adversely than loans secured by more stabilized assets. A substantial portion of our loans are secured by office space and similar commercial real estate. This sector has recently been affected by certain macroeconomic factors, such as an increased prevalence of remote work.
Assistant: