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 use software and other technology in our business that is licensed under open source license terms, and we may use more open source technology in the future. We do not currently distribute technology that includes open source, but we may do so in the future, either ourselves or through a partner. The terms of many open source licenses have not been interpreted by U.S. courts, and there is a risk that these licenses could be construed in a way that could impose unanticipated conditions or restrictions on our ability to commercialize products that include open source. As a result, we could be subject to lawsuits by parties claiming ownership of what we believe to be open source technology or claiming breach of open source licenses. Litigation could be costly for us to defend, harm our business and financial condition, or require us to devote additional research and development resources to change our products or services. In addition, if we were to combine our proprietary source code or other technology with open source technology in a certain manner, we could, under certain of the open source licenses, be required to release our source code or other proprietary technology to the public. This would allow our competitors to create similar products with less development effort and time. If we inappropriately use open source technology, or if the license terms for open source technology that we use change, we may be required to re-engineer our products or services, incur additional costs, discontinue the distribution of certain products or services or the availability of certain features or capabilities of our products or services, or take other remedial actions.
Assistant: