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: Our strategy focuses primarily on originating and making loans to, and making debt and equity investments in, U.S. middle market companies, with a focus on originated transactions sourced through the networks of our Adviser. Short transaction closing timeframes associated with originated transactions coupled with added tax or accounting structuring complexity and international transactions may result in higher risk in comparison to non-originated transactions. Most debt securities in which we intend to invest will not be rated by any rating agency and, if they were rated, they would be rated as below investment grade quality and are commonly referred to as “high yield” or “junk.” Debt securities rated below investment grade quality are generally regarded as having predominantly speculative characteristics and may carry a greater risk with respect to a borrower’s capacity to pay interest and repay principal. In addition, some of the loans in which we may invest may be “covenant-lite” loans. We use the term “covenant-lite” loans to refer generally to loans that do not have a complete set of financial maintenance covenants. Generally, “covenant-lite” loans provide borrower companies more freedom to negatively impact lenders because their covenants are incurrence-based, which means they are only tested and can only be breached following an affirmative action of the borrower, rather than by a deterioration in the borrower’s financial condition. Accordingly, to the extent we invest in “covenant-lite” loans, we may have fewer rights against a borrower and may have a greater risk of loss on such investments as compared to investments in or exposure to loans with financial maintenance covenants.
Assistant: