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: Our consolidated results of operations, financial position and cash flows are subject to fluctuations due to changes in foreign currency exchange rates. Historically, the majority of our revenue contracts are denominated in U.S. dollars, with the most significant exception being Japan, where we invoice primarily in the Japanese yen. Our expenses are generally denominated in the currencies in which our operations are located, which is primarily in the Americas and EMEA. Revenue resulting from selling in local currencies and costs incurred in local currencies are exposed to foreign currency exchange rate fluctuations that can affect our operating income. The currency exchange impact of the foreign exchange rates on our net income was $13 thousand favorable during the year ended December 31, 2020. The currency exchange impact of the foreign exchange rates on our net loss was $1.4 million and $0.7 million unfavorable during the years ended December 31, 2019 and 2018, respectively. As exchange rates vary, our operating income may differ from expectations. We deploy normal and customary hedging practices that are designed to proactively mitigate such exposure. The use of such hedging activities may not offset any, or more than a portion, of the adverse financial effects of unfavorable movements in currency exchange rates over the limited time the hedges are in place and would not protect us from long term shifts in currency exchange rates.
Assistant: