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: We may face negative publicity, including comments on social media, relating to aspects of our business, including, among others, food quality, public health concerns, restaurant facilities, customer complaints or litigation alleging illness or injury, health inspection scores, the integrity of our suppliers’ food processing and other policies, practices and procedures, employee relationships or other matters at one or more of our restaurants. Negative publicity generated against our restaurants may adversely affect us, regardless of whether the allegations are valid or whether we are held to be responsible. In addition, the negative impact of adverse publicity relating to one restaurant may extend beyond the restaurant involved to affect our other restaurants. A similar risk exists concerning food service businesses unrelated to us if customers mistakenly associate such unrelated businesses with our operations. Employee claims against us based on, among other things, wage and hour violations, discrimination, harassment, or wrongful termination may also create not only legal and financial liability but negative publicity that could adversely affect us and divert our financial and management resources that would otherwise be exerted in favor of our operations. These risks are amplified because of the prevalence of social media. Adverse social media comments and negative publicity could materially adversely affect our business, financial condition, results of operations and cash flows.
Assistant: