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 exposure to credit risk is primarily through cash and cash equivalents, restricted cash and accounts receivable, including unbilled balances. Our liquid assets are invested in cash, with a mix of local and international banks, and highly rated, short-term money market deposits, generally with original maturities of less than 90 days. We monitor the ratings of such investments and mitigate counterparty risks as appropriate. We extend credit to customers and other parties in the normal course of business and are thus subject to concentrations of customer credit risk. We have established various procedures to manage our credit exposure, including credit evaluations and maintaining an allowance for credit losses. We are also exposed to credit risk because our customers are concentrated in the oil and natural gas industry. This concentration of customers impacts overall exposure to credit risk because our customers may be similarly affected by changes in economic and industry conditions, including changes in oil and gas prices. We operate in approximately 60 countries and as such, our receivables are spread over many countries and customers. Accounts receivable in Algeria and the U.S. represented approximately 13% and 17%, respectively, of our net accounts receivable balance at December 31, 2022. No other country accounted for greater than 10% of our accounts receivable balance. Our customer base is comprised of a large number of IOC, NOC, Independents and service partners from all major oil and gas locations around the world. The majority of our accounts receivable are due for payment in less than 90 days and largely comprise amounts receivable from IOCs and NOCs. We closely monitor accounts receivable and raise provisions for expected credit losses where it is deemed appropriate.
Assistant: