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: Laws, regulations and other obligations (including applicable guidance, industry standards, external and internal privacy and security policies and contractual requirements) relating to personal data are constantly evolving, as federal, state, local and foreign governments continue to adopt new measures addressing data privacy, data security, and processing personal data. Existing privacy and data protection laws and regulations in the United States (including the California Consumer Privacy Act, as amended (“CCPA”)), Europe (including the E.U.’s General Data Protection Regulation) and other jurisdictions impose stringent obligations on such activities. For example, the CCPA, which applies to business representative and other types of personal data of California residents, provides for fines of up to $7,500 per intentional violation and allows private litigants affected by certain data breaches to recover significant statutory damages. Such laws and regulations may be interpreted or applied in a manner that is inconsistent with each other and may complicate our existing data management practices. Evolving compliance and operational requirements under the privacy laws of the jurisdictions in which we operate, regulations, and other obligations have become increasingly burdensome and complex. Privacy-related claims or lawsuits initiated by governmental bodies, customers or other third parties, irrespective of the merits, could be time consuming, result in costly enforcement actions (including regulatory proceedings, investigations, fines,penalties, audits, and inspections), litigation (including class action claims) or mass arbitration demands, penalties and fines, require us to change our business practices or cause business interruptions and may lead to administrative, civil, or criminal liability.
Assistant: