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 price of our common stock could decline as a result of sales of a large number of our common stock in the market, or the sale of securities convertible into a large number of our common stock. The perception that these sales could occur may also depress the market price of our common stock. As of December 31, 2020 we had outstanding 71,445,992 shares of redeemable convertible preferred stock with an aggregate liquidation preference of approximately $14.1 million, after accounting for the accumulated accreting return at a rate per annum equal to 7% on the accreted liquidation preference and paid in-kind. The aggregate accreting return will increase the number of shares of common stock issuable upon the conversion of the redeemable convertible preferred stock, which may result in a further decrease in the market value of our common stock. In addition, the terms of the redeemable convertible preferred stock provide that the conversion price may be reduced, which would result in the shares of redeemable convertible preferred stock being convertible into additional common stock upon certain events, including distributions on our common stock or issuances of additional common stock or equity-linked securities, at a price less than the then-applicable conversion price. The issuance of common stock upon conversion of the redeemable convertible preferred stock would result in immediate dilution to existing holders of our common stock, which dilution could be substantial. In addition, the market price of our common stock may be adversely affected by such factors as whether the market price is near or above the conversion price, which could make conversion of the shares of redeemable convertible preferred stock more likely.
Assistant: