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: The FDIC, the Federal Reserve and the Office of the Comptroller of the Currency have promulgated joint guidance on sound risk management practices for financial institutions with concentrations in commercial real estate lending. Under this guidance, a financial institution that, like us, is actively involved in commercial real estate lending should perform a risk assessment to identify concentrations. A financial institution may have a concentration in commercial real estate lending if, among other factors (i) total reported loans for construction, land development, and other land represent 100% or more of total capital, or (ii) total reported loans secured by multifamily and non-farm/non-residential properties, loans for construction, land development and other land, and loans otherwise sensitive to the general commercial real estate market, including loans to commercial real estate related entities, represent 300% or more of total capital. Our total loans for multifamily, non-farm/non-residential, construction, land development and other land represented 292.3% of total risk-based capital at June 30, 2023. The particular focus of the guidance is on exposure to commercial real estate loans that are dependent on the cash flow from the real estate held as collateral and that are likely to be at greater risk to conditions in the commercial real estate market (as opposed to real estate collateral held as a secondary source of repayment or as an abundance of caution). The purpose of the guidance is to assist banks in developing risk management practices and capital levels commensurate with the level and nature of real estate concentrations. The guidance states that management should employ heightened risk management practices including Board and management oversight and strategic planning, development of underwriting standards, risk assessment and monitoring through market analysis and stress testing. While we believe we have implemented policies and procedures with respect to our commercial real estate loan portfolio consistent with this guidance, bank regulators could require us to implement additional policies and procedures pursuant to their interpretation of the guidance that may result in additional costs to us.
Assistant: