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 dependent on a small number of customers for a large portion of our revenues. A significant decrease in the sales to or loss of any of our major customers would have a material adverse effect on our business and results of operations. In fiscal 2021, Raytheon Technologies accounted for 19% of our total net revenues, Lockheed Martin Corporation accounted for 15% of our total net revenues, and the US Navy accounted for 12% of our total net revenues. In fiscal 2020, both Lockheed Martin Corporation and Raytheon Technologies accounted for 16% of our total net revenues. In fiscal 2019, Raytheon Technologies accounted for 20% of our total net revenues and Lockheed Martin Corporation accounted for 17% of our total net revenues. Customers in the defense market generally purchase our products in connection with government programs that have a limited duration, leading to fluctuating sales to any particular customer in this market from year to year. In addition, our revenues are largely dependent upon the ability of customers to develop and sell products that incorporate our products. No assurance can be given that our customers will not experience financial, technical or other difficulties that could adversely affect their operations and, in turn, our results of operations. Additionally, on a limited number of programs the customer has co-manufacturing rights which could lead to a shift of production on such a program away from us which in turn could lead to lower revenues.
Assistant: