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 subject to the growing risk of climate change. Among the risks associated with climate change are more frequent severe weather events. Severe weather events such as hurricanes, tropical storms, tornados, winter storms, freezes, flooding and other large-scale weather catastrophes in our markets subject us to significant risks and more frequent severe weather events magnify those risks. Large-scale weather catastrophes or other significant climate change effects that either damage or destroy residential or multifamily real estate underlying mortgage loans or real estate collateral, could decrease the value of our real estate collateral or increase our delinquency rates in the affected areas and thus diminish the value of our loan portfolio. In addition, the effects of climate change may have a significant effect on our geographic markets, and could disrupt our operations or the operations of our customers, third party service providers, or supply chains more generally. Those disruptions could result in declines in economic conditions in our geographic markets or industries in which our borrowers operate and impact their ability to repay loans or maintain deposits. Climate change could also impact our assets or employees directly or lead to changes in customer preferences that could negatively affect our growth or business strategies. In addition, our reputation and customer relationships could be damaged due to our practices related to climate change, including our or our customers’ involvement in certain industries or projects associated with causing or exacerbating climate change.
Assistant: