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: The market prices for the securities of biotechnology companies, including ours, have historically been volatile. The market has from time to time experienced significant price and volume fluctuations that are unrelated to the operating performance of any particular company. The trading price of the common shares could continue to be subject to wide fluctuations in price in response to various factors, many of which are beyond our control, including the results and adequacy of our pre-clinical studies and clinical trials, as well as those of our collaborators, or our competitors; the results of our operations, such as quarterly or annual sales figures; other evidence of the safety or effectiveness of LUPKYNIS or those of our competitors; announcements of technological innovations or new products by our competitors; governmental regulatory actions; developments with collaborators; developments (including litigation) concerning our patents or other proprietary rights of competitors; period-to-period fluctuations in operating results; guidance we may provide as to the commercial performance of LUPKYNIS; changes in estimates of our performance by securities analysts; market conditions for biotechnology stocks in general; global or local political, economic, social and health crises; market rumors; and other factors not within our control could impact the market price of the common shares, regardless of our operating performance. In the past, following periods of volatility in the market price of a company’s securities, securities class action litigation has often been instituted. A class action suit against us could result in substantial costs, potential liabilities and the diversion of management’s attention and resources.
Assistant: