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: There is increasing concern that a gradual rise in global average temperatures due to increased concentration of carbon dioxide and other greenhouse gases in the atmosphere will cause significant changes in weather patterns around the globe, an increase in the frequency, severity, and duration of extreme weather conditions and natural disasters, and water scarcity and poor water quality. These events could adversely impact the cultivation of cotton, which is a key resource in the production of our products, disrupt the operation of our supply chain and the productivity of our contract manufacturers, increase our production costs, impose capacity restraints and impact the types of apparel products that consumers purchase. These events could also compound adverse economic conditions and impact consumer confidence and discretionary spending. As a result, the effects of climate change could have a long-term adverse impact on our business and results of operations. In many countries, governmental bodies are enacting new or additional legislation and regulations to reduce or mitigate the potential impacts of climate change. If we, our suppliers, or our contract manufacturers are required to comply with these laws and regulations, or if we choose to take voluntary steps to reduce or mitigate our impact on climate change, we may experience increases in energy, production, transportation, and raw material costs, capital expenditures, or insurance premiums and deductibles, which could adversely impact our operations. Inconsistency of legislation and regulations among jurisdictions may also affect the costs of compliance with such laws and regulations. Any assessment of the potential impact of future climate change legislation, regulations or industry standards, as well as any international treaties and accords, is uncertain given the wide scope of potential regulatory change in the countries in which we operate.
Assistant: