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 are exposed to market risk from material movements in foreign exchange rates between the U.S. dollar and the currencies of the foreign countries in which we operate. In fiscal 2021, approximately 23% of our total expenses were in currencies other than the U.S. dollar. As a result of our extensive operations in Mexico, our primary risk relates to changes in the rates between the U.S. dollar and the Mexican peso. To mitigate this currency risk, we enter into forward foreign exchange contracts to exchange U.S. dollars for Mexican pesos. We also enter into forward foreign exchange contracts to exchange U.S. dollars for Chinese yuan in order to mitigate risk related to our purchases and payments to our Chinese vendors. The extent to which we use forward foreign exchange contracts is periodically reviewed in light of our estimate of market conditions and the terms and length of anticipated requirements. The use of derivative financial instruments allows us to reduce our exposure to the risk that the eventual net cash outflow resulting from funding the expenses of the foreign operations will be materially affected by changes in the exchange rates. We do not engage in currency speculation or hold or issue financial instruments for trading purposes. These contracts generally expire in a year or less. Any change in the fair value of foreign exchange contracts is accounted for as an increase or decrease to “foreign exchange impact of lease liabilities and forward contracts” in the consolidated statements of operations. We recorded a non-cash gain of $7,713,000 and a non-cash loss of $6,491,000 due to the change in the fair value of the forward foreign currency exchange contracts during fiscal 2021 and 2020, respectively. In addition, we recorded a gain of $9,893,000 and a loss of $11,710,000 in connection with the remeasurement of foreign currency-denominated lease liabilities during fiscal 2021 and 2020, respectively.
Assistant: