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 are or have been a defendant in a number of lawsuits, including, among others, purported class action lawsuits for alleged antitrust violations and violations of federal securities laws, product liability claims (which may involve lawsuits seeking class action status or seeking to establish multi-district litigation proceedings, including pending claims relating to our hernia repair implant products, surgical continence and pelvic organ prolapse products for women, vena cava filter products and implantable ports), and suits alleging patent infringement. We also are or have been subject to government subpoenas and civil investigative demands seeking information with respect to alleged violations of law, including in connection with federal and/or state healthcare programs (such as Medicare or Medicaid), federal contracting requirements and/or sales and marketing practices. A more detailed description of certain litigation to which we are a party is contained in Note 6 to the consolidated financial statements included in Item 8. Financial Statements and Supplementary Data. We could be subject to additional lawsuits, governmental investigations, subpoenas and civil investigative demands in the future. Any such lawsuits, governmental investigations, subpoenas and civil investigative demands could ultimately have a material adverse effect on our results of operations, financial condition and liquidity, and could distract management from the operations of the business.
Assistant: