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 have a substantial amount of goodwill on our balance sheet as a result of acquisitions we have completed. Approximately 99% of this goodwill is concentrated in our Truck Segment. The carrying value of goodwill represents the fair value of an acquired business in excess of identifiable assets and liabilities as of the acquisition date. Goodwill is not amortized, but instead is evaluated for impairment at least annually, or more frequently if potential interim indicators exist that could result in impairment. In testing for impairment, if the carrying value of a reporting unit exceeds its current fair value as determined based on the discounted future cash flows of the reporting unit, the goodwill is considered impaired and is reduced to fair value via a non-cash charge to earnings. Events and conditions that could result in impairment include weak economic activity, adverse changes in the regulatory environment, any matters that impact the ability of the manufacturers we represent to provide us with commercial vehicles or parts, issues with our franchise rights, or other factors leading to reductions in expected long-term sales or profitability. Determination of the fair value of a reporting unit includes developing estimates that are highly subjective and incorporate calculations that are sensitive to minor changes in underlying assumptions. Changes in these assumptions or a change in the Company’s reportable segments could result in an impairment charge in the future, which could have a significant adverse impact on our reported earnings. See “Management’s Discussion and Analysis of Financial Condition and Results of Operations — Critical Accounting Policies and Estimates — Goodwill” for more information regarding the potential impact of changes in assumptions.
Assistant: