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: At December 31, 2020, agricultural loans, including agricultural real estate and operating loans, were $21.4 million, or 1.3% of total loans. Agricultural lending involves a greater degree of risk and typically involves higher principal amounts than other types of loans. Repayment is dependent upon the successful operation of the business, which is greatly dependent on many things outside the control of either us or the borrowers. These factors include adverse weather conditions that prevent the planting of a crops or limit crop yields (such as hail, drought and floods), loss of livestock due to disease or other factors, declines in market prices for agricultural products (both domestically and internationally) and the impact of government regulations (including changes in price supports, subsidies, tariffs and environmental regulations). In addition, many farms are dependent on a limited number of key individuals whose injury or death may significantly affect the successful operation of the farm. If the cash flow from a farming operation is diminished, the borrower’s ability to repay the loan may be impaired. Consequently, agricultural loans may involve a greater degree of risk than other types of loans, particularly in the case of loans that are unsecured or secured by rapidly depreciating assets such as farm equipment (some of which is highly specialized with a limited or no market for resale), or assets such as livestock or crops. In such cases, any repossessed collateral for a defaulted agricultural operating loan may not provide an adequate source of repayment of the outstanding loan balance as a result of the greater likelihood of damage, loss or depreciation or because the assessed value of the collateral exceeds the eventual realization value.
Assistant: