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 operations and financial performance of projects in the renewable energy sectors may be affected by the prices of energy commodities, such as natural gas, wholesale electricity and other energy-related products. For example, the price of renewable energy resources changes in relation to the market prices of natural gas and electricity. The market price for natural gas is sensitive to cyclical demand and capacity supply, changes in weather patterns, natural gas storage levels, natural gas production levels, general economic and geopolitical conditions (including the current conflicts in the Middle East and Ukraine) and the volume of natural gas imports and exports. The market price of electricity is sensitive to cyclical changes in demand and capacity supply, and in the economy and geopolitical conditions (including the current conflicts in the Middle East and Ukraine), as well as to regulatory trends and developments impacting electricity market rules and pricing, transmission development and investment to power markets within the United States and in other jurisdictions through interconnects and other external factors outside of the control of renewable energy power-producing projects. Volatility of commodity prices also creates volatility in the prices of Environmental Attributes, which are inversely related to the wholesale price of unleaded gasoline. In addition, volatility of commodity prices, such as the market price of gas and electricity, may also make it more difficult for us to raise any additional capital for our renewable energy projects that may be necessary to operate, to the extent that market participants perceive that a project’s performance may be tied directly or indirectly to commodity prices. Accordingly, the potential revenues and cash flows of these projects may be volatile and adversely affect the value of our investments.
Assistant: