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: Our sales are typically made pursuant to standard purchase orders and/or specified customer contracts for delivery of products and not under long-term supply arrangements with our customers. Our customers may seek to cancel or defer orders before shipment. Additionally, we sell a portion of our products through third-party distributors, some of whom have rights to return products if the product is nonconforming. We may purchase and manufacture inventory based on estimates of customer demand for our products, which is difficult to predict and may not be accurate. The difficulties of forecasting may be compounded when we sell to OEMs indirectly through distributors or contract manufacturers, or both, as our forecasts of demand will then be based on estimates provided by multiple parties. In addition, our customers and distributors may change their inventory practices on short notice for any reason. Many of our products are customized to the needs or specifications of a specific customer or have a limited number of potential buyers. The cancellation or deferral of product orders, the return of previously sold products, overproduction due to a change in anticipated order volumes could result in us holding excess or obsolete inventory, which could result in inventory write-downs and, in turn, could have a material adverse effect on our financial condition. On the other hand, customers may require rapid increases in production on short notice, which could result in damaged customer relationships, increased manufacturing costs, increased liabilities, or harm to our reputation if we are unable to meet such increases in demand.
Assistant: