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 sell nearly all of the shredded paper from our secure information destruction business to paper companies and recycled paper brokers. SOP is marketed as a commodity and is subject to significant demand and price fluctuations beyond our control. Additionally, the market demand for recycled paper can be volatile due to factors beyond our control. Historically, economic and market shifts, fluctuations in capacity and changes in foreign currency exchange rates have created cyclical changes in prices, volume, revenues, and margins for pulp and paper products. The length and magnitude of industry cycles have varied over time and by product, but generally reflect changes in macroeconomic conditions and levels of industry capacity. The overall levels of demand for the pulp and paper products reflect fluctuations in levels of end-user demand, which depend in part on general macroeconomic conditions in North America and worldwide. We have experienced a decline in paper tonnage collected over the past several years which we believe is a reduction in the consumption of paper due to an increase in the use of computers and digital technology and pandemic related impacts, such as a shift to remote work and virtual learning, and it remains unclear what the future long-term impact will be on the paper volume we collect. Lack of demand for our shredded paper material or increasing uses of substitutes for SOP could adversely affect our business, our results of operations and financial condition.
Assistant: