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: Our relationships with our customers and our reputation are based, in part, on perceptions of subjective qualities. Incidents involving us, our retail banners, our executives and other Associates, our board of directors, our policies and practices, our third-party providers, our vendors and others within our supply chain, the merchandise and brands, including our licensed or owned brands, that we sell, our investments, in regions where we have operations or investments, our partners and our industry more generally that erode trust or confidence could adversely affect our reputation and thereby impact our business, particularly if the incidents result in rapid or significant adverse publicity, protest, litigation or governmental inquiry. Information on such incidents that is publicized through traditional or digital media platforms, including social media, websites, blogs and other forums that facilitate rapid, broad communications to an audience of consumers and other interested persons, may adversely affect our reputation and brand, even if the information is inaccurate, incomplete or unverified. Similarly, challenges or reactions to action (or inaction), or perceived action (or inaction), by our company to crises, including the Russian invasion of Ukraine or a public health crisis like the COVID-19 pandemic, or on issues like corporate responsibility, responsible sourcing, environmental sustainability, climate change, inclusion and diversity, racial justice and equity, human rights, politics and lobbying, privacy, merchandising, product safety, compensation and benefits, workplace environment, labor compliance, workforce reductions or other employment actions, or other sensitive topics, and any perceived lack of transparency about such matters, could harm our reputation, particularly as expectations of corporate action and of companies’ responsibilities in areas related to environmental, social and governance (“ESG”) issues have changed and may continue to change.
Assistant: