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: Variations in the price of methane gas and other energy-related products that are marketed and sold by our landfill gas recovery operations affect our results. Pursuant to the Energy Independence and Security Act of 2007, the United States EPA has promulgated the Renewable Fuel Standards, or RFS, which require refiners to either blend "renewable fuels," such as ethanol and biodiesel, into their transportation fuels or to purchase renewable fuel credits, known as renewable identification numbers, or RINs, in lieu of blending. In some cases, landfill gas generated at our landfills in the United States and Canada qualifies as a renewable fuel for which RINs are available. The price of RINs has been extremely volatile and is dependent upon a variety of factors, including potential legislative changes, the availability of RINs for purchase, the demand for RINs, which is dependent on transportation fuel production levels, the mix of the petroleum business’ petroleum products and fuel blending performed at the refineries and downstream terminals, all of which can vary significantly from period to period. In addition, demand for RINs can be impacted by the ability of refineries to obtain small refinery exemptions, or SREs, through the EPA. Any reductions or limitations on the requirement to blend renewable fuel and any related waivers including SREs, would likely reduce the demand for RINs, which could impact the value of RINs. Pursuant to the Canadian Environmental Protection Act, 1999, the Canadian federal government has promulgated the Clean Fuel Regulations (CFRs), which will replace the Renewable Fuel Regulations. Under the CFRs, gasoline and diesel producers and importers (primary suppliers) must lower the carbon intensity of the gasoline and diesel that they produce in Canada and/or import in accordance with prescribed limits through the use of compliance credits. Compliance credits can be created by primary suppliers or acquired from other registered creators of credits in accordance with the credit-creating mechanisms set out in the CFRs. At this time, we do not know how the new CFRs in Canada will impact the demand for, or value of, our renewable fuel in the future.
Assistant: