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: Along with our own data and information in the normal course of our business, we collect and retain certain data that is subject to specific laws and regulations. The compliant processing of this data domestically and transferring of this data across international borders continues to increase in complexity. This data is subject to regulation at various levels of government in many areas of our business and in jurisdictions across the world, including data privacy and security laws such as the California Consumer Privacy Act (“CCPA”), the California Privacy Rights Act (“CPRA”), the EU General Data Protection Regulation (“GDPR”), the U.K. and General Data Protection Regulation (“U.K. GDPR”), the standard contractual clauses (“SCC”) adopted by the European Commission and the U.K. Parliament for the processing and transfer of personal data in compliance with the GDPR and/or the U.K. GDPR, and Quebec’s Bill 64 (“Bill 64”). We also operate, or may in the future operate, in other jurisdictions that have issued, or are considering issuing, data privacy laws and regulations. The U.S. Federal Trade Commission recently adopted rules requiring the reporting of certain data breaches that may apply to our operations and those of our subsidiaries. As the number and complexities of such laws and regulations continue to increase, we will face increasingly complex compliance, monitoring, and control obligations. As the implementation, interpretation, and enforcement of such laws continues to progress and evolve, there may also be developments that amplify such risks. Any failure by us to comply with these laws and regulations, including as a result of a security or privacy breach, or otherwise, could expose us to litigation and enforcement, and result in significant penalties, fines, and other liabilities.
Assistant: