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 face risks arising from various litigation matters and other claims that have been asserted against us or that may be asserted against us in the future, including, but not limited to, claims for product liability, patent and trademark infringement, antitrust, warranty, contract and third-party property damage or personal injury, including claims arising from the matters described in Note 5 to our consolidated financial statements included elsewhere in this Annual Report on Form 10-K. For instance, we have seen a continuing nationwide trend in purported class actions against chemical manufacturers generally seeking relief such as medical monitoring, property damages, off-site remediation and punitive damages arising from alleged environmental torts without claiming present personal injuries. We have also seen a continuing trend in public and private nuisance suits being filed on behalf of states, counties, cities and utilities alleging harm to the general public. In addition, various factors or developments can lead to changes in current estimates of liabilities such as a final adverse judgment, significant settlement or changes in applicable law. A future adverse ruling or unfavorable development could result in future charges that could have a material adverse effect on us. An adverse outcome in any one or more of these matters could be material to our business, financial condition, results of operations and cash flows. In particular, product liability claims, regardless of their merits, could be costly, divert management's attention and adversely affect our reputation and demand for our products.
Assistant: