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: Because our software is complex, undetected errors, failures or bugs may occur. Our software is often installed and used with different operating systems, system management software, and equipment and networking configurations, which may cause errors or failures of our software or other aspects of the computing environment into which it is deployed. In addition, deployment of our software into computing environments may expose undetected errors, compatibility issues, failures or bugs in our software. Despite our testing, errors, failures or bugs may not be found in our software until it is released to our customers. Moreover, our customers could incorrectly implement or inadvertently misuse our software, which could result in customer dissatisfaction and adversely impact the perceived utility of our products as well as our brand. Any of these real or perceived errors, compatibility issues, failures or bugs in our software could result in negative publicity, reputational harm, loss of or delay in market acceptance of our software, loss of competitive position or claims by customers for losses sustained by them. In any such event, we may be required, or may choose, for customer relations or other reasons, to expend additional resources in order to correct the problem. Alleviating any of these problems could require significant expenditures of our capital and other resources and could cause interruptions or delays in the use of our solutions, which could cause us to lose existing or potential customers and could adversely affect our operating results and growth prospects.
Assistant: