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: In the normal course of business we control, process, or have access to personal information regarding our own employees or employment candidates, as well as that of many of our customers or managed suppliers. Information concerning these individuals may also reside in systems controlled by third parties for purposes such as employee benefits and payroll administration. The legal and regulatory environment concerning data privacy is becoming more complex and challenging, and the potential consequences of non-compliance have become more severe. The European Union’s General Data Protection Regulation, the California Consumer Privacy Act and similar laws impose additional compliance requirements related to the collection, use, processing, transfer, disclosure, and retention of personal information, which can increase operating costs and resources to accomplish. Any failure to abide by these regulations or to protect such personal information from inappropriate access or disclosure, whether through social engineering or by accident or other cause, could have severe consequences including fines, litigation, regulatory sanctions, reputational damage, and loss of customers or employees. Although we have a program designed to preserve the privacy rights of the personal data that we control or process, as well as personal data that we entrust to third parties, there can be no assurance that our program will meet all current and future regulatory requirements, anticipate all potential methods of unauthorized access, or prevent all inappropriate disclosures. Our insurance coverage may not be sufficient to cover all such costs or consequences, and there can be no assurance that any insurance that we now maintain will remain available under acceptable terms.
Assistant: