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 electric mobility industry is subject to rapidly changing and often complex regulatory environments at local, state, national, and international levels. Evolving regulations related to safety standards, emissions, licensing, and operational requirements can have a substantial impact on our business operations and profitability. Compliance with these changing regulations may necessitate costly modifications to our products, business processes, or market strategies, which could lead to increased expenses and delays in product development and market entry. Failure to navigate and adhere to evolving regulations adequately could result in legal and financial liabilities, damage to our reputation, and potential market restrictions. Furthermore, inconsistency in regulations between different jurisdictions may create challenges in maintaining uniform business practices and product offerings, increasing our exposure to regulatory risks. Furthermore, a significant portion of our customer base comprises food delivery workers, and if leading food delivery platforms like Uber Eats and DoorDash impose new requirements on the type of electric vehicles they allow, non-compliance on our part could result in the loss of these customers. While we believe we are presently in compliance with applicable laws and regulations in our operating regions, there can be no assurance that we can always promptly adapt to the rapidly changing regulatory environment. If we fail to effectively adjust to the changing regulatory landscape and comply with applicable laws and regulations in our operating regions, our business, prospects, financial condition and operating results would be materially and adversely affected.
Assistant: