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 and our subsidiaries may, subject to any limitations in the terms of our existing loan facilities or the Senior Secured Credit Facilities, incur additional debt, secure existing or future debt, recapitalize our debt or take a number of other actions that are not limited by the terms of our term loans that could have the effect of diminishing our ability to make payments under the indebtedness when due. If we incur any additional debt, the related risks that we and our subsidiaries face could intensify. We plan to finance the cash portion of the purchase price of the merger with Silicon Motion with approximately $3.5 billion of cash on hand and new debt. In connection with entering into the Merger Agreement, we entered into a commitment letter, dated as of May 5, 2022, and amended on June 17, 2022 and October 24, 2022 with Wells Fargo Bank, N.A. and Wells Fargo Securities, LLC, or collectively, Wells Fargo, pursuant to which, subject to the terms and conditions set forth therein, Wells Fargo has committed to provide us (i) a senior secured term B loan facility in an aggregate principal amount of up to $2.7375 billion, (ii) a senior secured term A loan facility in an aggregate principal amount of up to $512.5 million, and (iii) a senior secured revolving credit facility in an aggregate principal amount of up to $250.0 million. The funding of these secured credit facilities provided for in the commitment letter is contingent on the satisfaction of customary conditions, including (i) the execution and delivery of definitive documentation with respect to such credit facilities in accordance with the terms sets forth in the commitment letter and (ii) the consummation of the merger in accordance with the Merger Agreement.
Assistant: