state listlengths 2 52 | action dict | next_obs listlengths 2 2 | state_len int64 874 5.07k | temperature float64 1 1 | reward float64 0.08 1 | done bool 2
classes | truncated bool 1
class | timestep int64 0 25 | try_step int64 0 0 | batch_id int64 60 60 | unique_data_sample_id int64 0 31 | generation_id int64 0 0 | split stringclasses 1
value | return_ float64 0.08 1 | advantage float64 0.08 1 | return_is_computed bool 1
class | advantage_is_computed bool 1
class | constant_reward_group bool 1
class | tools listlengths 5 5 | action_prob float64 0.08 1 | system_prompt null |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
[
{
"content": "Only execute one tool call at a time. Think and reason step by step. Feel free to iteratively gather data as much as you need to answer the question. Although there is a limit of 30 turns, you can still gather data as much as you need to answer the question. When you have gathered all the data, an... | {
"content": "I need to find out which tables are available for Tesla to look for information about valuation allowance for deferred tax assets. The valuation allowance is likely stored in a financials-related table.\n\n<tool_call>\n{\"name\": \"get_descriptions\", \"arguments\": {\"company_name\": \"tesla\"}}\n</too... | [
{
"content": "[\"us_gaap_DebtInstrumentRedemptionTableTextBlock\", \"us_gaap_ScheduleOfComponentsOfIncomeTaxExpenseBenefitTableTextBlock\", \"sla_ScheduleOfAccruedLiabilitiesAndOtherCurrentLiabilitiesTableTextBlock\", \"us_gaap_LesseeOperatingLeaseLiabilityMaturityTableTextBlock\", \"us_gaap_ScheduleOfDeferredT... | 891 | 1 | 0.913101 | false | false | 0 | 0 | 60 | 0 | 0 | train_all | 0.913101 | 0.913101 | true | true | false | [
{
"description": "Get a list of possible texts to look up for. Each text contains a singular table that is described by its complete name.",
"name": "get_descriptions",
"parameters": {
"properties": {
"company_name": {
"description": "The name of the company to get the table name... | 0.913101 | null |
[
{
"content": "Only execute one tool call at a time. Think and reason step by step. Feel free to iteratively gather data as much as you need to answer the question. Although there is a limit of 30 turns, you can still gather data as much as you need to answer the question. When you have gathered all the data, an... | {
"content": "The table \"us_gaap_ScheduleOfDeferredTaxAssetsAndLiabilitiesTableTextBlock\" is likely to contain information about deferred tax assets and liabilities, including any valuation allowance. I will retrieve its metadata to understand its structure and identify relevant columns.\n\n<tool_call>\n{\"name\": ... | [
{
"content": "{\"description\": \"deferred_tax_assets_liabilities_as_of_december_31_2024_and_2023_consisted_of_the_following_in_millions\",\"column_names\": [\"item\",\"december_31_2024\",\"december_31_2023\"],\"unique_vals_per_col\": {\"item\": [\"deferred_tax_assets:\",\"net_operating_loss_carry_forwards\",\"... | 1,487 | 1 | 1 | false | false | 1 | 0 | 60 | 0 | 0 | train_all | 1 | 1 | true | true | false | [
{
"description": "Get a list of possible texts to look up for. Each text contains a singular table that is described by its complete name.",
"name": "get_descriptions",
"parameters": {
"properties": {
"company_name": {
"description": "The name of the company to get the table name... | 1 | null |
[
{
"content": "Only execute one tool call at a time. Think and reason step by step. Feel free to iteratively gather data as much as you need to answer the question. Although there is a limit of 30 turns, you can still gather data as much as you need to answer the question. When you have gathered all the data, an... | {
"content": "I need to extract specific values related to the valuation allowance and deferred tax assets as of December 31, 2024. The query will fetch the relevant rows for items like 'valuation_allowance', 'total_deferred_tax_assets', and others to understand the context and magnitude of the valuation allowance.\n... | [
{
"content": "[{\"item\":\"total_deferred_tax_assets\",\"december_31_2024\":\"$11,962\"},{\"item\":\"valuation_allowance\",\"december_31_2024\":\"($1,224)\"},{\"item\":\"deferred_tax_assets_net_of_valuation_allowance\",\"december_31_2024\":\"$10,738\"},{\"item\":\"deferred_tax_assets_liabilities_net_of_valuatio... | 1,328 | 1 | 0.657585 | false | false | 2 | 0 | 60 | 0 | 0 | train_all | 0.657585 | 0.657585 | true | true | false | [
{
"description": "Get a list of possible texts to look up for. Each text contains a singular table that is described by its complete name.",
"name": "get_descriptions",
"parameters": {
"properties": {
"company_name": {
"description": "The name of the company to get the table name... | 0.657585 | null |
[
{
"content": "Only execute one tool call at a time. Think and reason step by step. Feel free to iteratively gather data as much as you need to answer the question. Although there is a limit of 30 turns, you can still gather data as much as you need to answer the question. When you have gathered all the data, an... | {
"content": "I need to compare the valuation allowance as of December 31, 2024, with the previous year (2023) to understand the trend. This will provide context on whether management's assessment of future tax benefits has changed.\n\n<tool_call>\n{\"name\": \"sql_query\", \"arguments\": {\"company_name\": \"tesla\"... | [
{
"content": "[{\"item\":\"total_deferred_tax_assets\",\"december_31_2023\":\"$10,774\"},{\"item\":\"valuation_allowance\",\"december_31_2023\":\"($892)\"},{\"item\":\"deferred_tax_assets_net_of_valuation_allowance\",\"december_31_2023\":\"$9,882\"}]",
"role": "tool"
},
{
"content": "<tool_call>\n{\... | 1,386 | 1 | 0.945704 | false | false | 3 | 0 | 60 | 0 | 0 | train_all | 0.945704 | 0.945704 | true | true | false | [
{
"description": "Get a list of possible texts to look up for. Each text contains a singular table that is described by its complete name.",
"name": "get_descriptions",
"parameters": {
"properties": {
"company_name": {
"description": "The name of the company to get the table name... | 0.945704 | null |
[
{
"content": "Only execute one tool call at a time. Think and reason step by step. Feel free to iteratively gather data as much as you need to answer the question. Although there is a limit of 30 turns, you can still gather data as much as you need to answer the question. When you have gathered all the data, an... | {
"content": "I need to calculate the significance of the valuation allowance as a percentage of total deferred tax assets as of December 31, 2024. The calculation will be (valuation_allowance / total_deferred_tax_assets) * 100. The result will show the relative size of the valuation allowance, which indicates manage... | [
{
"content": "[10.23240260825949, \"Calculated: (1224/11962) * 100 = 10.23240260825949\"]",
"role": "tool"
},
{
"content": "<tool_call>\n{\"name\": \"calculator\", \"arguments\": {\"expression\": \"((1224-892)/892) * 100\"}}\n</tool_call>",
"role": "assistant"
}
] | 1,518 | 1 | 0.376336 | false | false | 4 | 0 | 60 | 0 | 0 | train_all | 0.376336 | 0.376336 | true | true | false | [
{
"description": "Get a list of possible texts to look up for. Each text contains a singular table that is described by its complete name.",
"name": "get_descriptions",
"parameters": {
"properties": {
"company_name": {
"description": "The name of the company to get the table name... | 0.376336 | null |
[
{
"content": "Only execute one tool call at a time. Think and reason step by step. Feel free to iteratively gather data as much as you need to answer the question. Although there is a limit of 30 turns, you can still gather data as much as you need to answer the question. When you have gathered all the data, an... | {
"content": "I need to calculate the percentage change in the valuation allowance from 2023 to 2024 to understand if management's assessment of future tax benefits has become more or less conservative. The formula is ((2024 valuation allowance - 2023 valuation allowance) / 2023 valuation allowance) * 100.\n\n<tool_c... | [
{
"content": "[37.219730941704036, \"Calculated: ((1224-892)/892) * 100 = 37.219730941704036\"]",
"role": "tool"
},
{
"content": "<tool_call>\n{\"name\": \"calculator\", \"arguments\": {\"expression\": \"(1224/10738) * 100\"}}\n</tool_call>",
"role": "assistant"
}
] | 1,615 | 1 | 0.634536 | false | false | 5 | 0 | 60 | 0 | 0 | train_all | 0.634536 | 0.634536 | true | true | false | [
{
"description": "Get a list of possible texts to look up for. Each text contains a singular table that is described by its complete name.",
"name": "get_descriptions",
"parameters": {
"properties": {
"company_name": {
"description": "The name of the company to get the table name... | 0.634536 | null |
[
{
"content": "Only execute one tool call at a time. Think and reason step by step. Feel free to iteratively gather data as much as you need to answer the question. Although there is a limit of 30 turns, you can still gather data as much as you need to answer the question. When you have gathered all the data, an... | {
"content": "I need to verify the significance of the valuation allowance as a percentage of total deferred tax assets in 2024. The calculation will be (valuation_allowance / total_deferred_tax_assets) * 100. This will confirm the magnitude of the valuation allowance relative to the total deferred tax assets.\n\n<to... | [
{
"content": "[11.398770720804619, \"Calculated: (1224/10738) * 100 = 11.398770720804619\"]",
"role": "tool"
},
{
"content": "<tool_call>\n{\"name\": \"respond_user\", \"arguments\": {\"text\": \"As of December 31, 2024 Tesla reported total deferred tax assets of $11,962 million and a valuation allo... | 1,743 | 1 | 0.575204 | false | false | 6 | 0 | 60 | 0 | 0 | train_all | 0.575204 | 0.575204 | true | true | false | [
{
"description": "Get a list of possible texts to look up for. Each text contains a singular table that is described by its complete name.",
"name": "get_descriptions",
"parameters": {
"properties": {
"company_name": {
"description": "The name of the company to get the table name... | 0.575204 | null |
[
{
"content": "Only execute one tool call at a time. Think and reason step by step. Feel free to iteratively gather data as much as you need to answer the question. Although there is a limit of 30 turns, you can still gather data as much as you need to answer the question. When you have gathered all the data, an... | {
"content": "I have gathered all the necessary data and calculations. I now provide a comprehensive and accurate summary of Tesla's valuation allowance for deferred tax assets as of December 31, 2024, including its significance and implications for management's assessment of future tax benefits.\n\n<tool_call>\n{\"n... | [
{
"content": "",
"role": "assistant"
},
{
"content": "",
"role": "assistant"
}
] | 1,852 | 1 | 0.114676 | true | false | 7 | 0 | 60 | 0 | 0 | train_all | 0.114676 | 0.114676 | true | true | false | [
{
"description": "Get a list of possible texts to look up for. Each text contains a singular table that is described by its complete name.",
"name": "get_descriptions",
"parameters": {
"properties": {
"company_name": {
"description": "The name of the company to get the table name... | 0.114676 | null |
[
{
"content": "Only execute one tool call at a time. Think and reason step by step. Feel free to iteratively gather data as much as you need to answer the question. Although there is a limit of 30 turns, you can still gather data as much as you need to answer the question. When you have gathered all the data, an... | {
"content": "I need to find out what tables are available for Meta to understand their lease financing strategy. This will help me identify relevant data about lease financing over the years 2022 and 2024.\n\n<tool_call>\n{\"name\": \"get_descriptions\", \"arguments\": {\"company_name\": \"meta\"}}\n</tool_call>",
... | [
{
"content": "[\"srt_ContractualObligationFiscalYearMaturityScheduleTableTextBlock\", \"us_gaap_ScheduleOfComponentsOfIncomeTaxExpenseBenefitTableTextBlock\", \"us_gaap_LesseeOperatingLeaseLiabilityMaturityTableTextBlock\", \"us_gaap_ScheduleOfDeferredTaxAssetsAndLiabilitiesTableTextBlock\", \"us_gaap_ScheduleO... | 884 | 1 | 1 | false | false | 0 | 0 | 60 | 1 | 0 | train_all | 1 | 1 | true | true | false | [
{
"description": "Get a list of possible texts to look up for. Each text contains a singular table that is described by its complete name.",
"name": "get_descriptions",
"parameters": {
"properties": {
"company_name": {
"description": "The name of the company to get the table name... | 1 | null |
[
{
"content": "Only execute one tool call at a time. Think and reason step by step. Feel free to iteratively gather data as much as you need to answer the question. Although there is a limit of 30 turns, you can still gather data as much as you need to answer the question. When you have gathered all the data, an... | {
"content": "The table \"meta_LeaseBalanceSheetInformationTableTextBlock\" is likely to contain lease-related balance sheet information, which could include lease liabilities and right-of-use assets over time. I should examine its structure to see if it has columns for years like 2022 and 2024.\n\n<tool_call>\n{\"na... | [
{
"content": "{\"description\": \"supplemental_balance_sheet_information_related_to_lease_liabilities\",\"column_names\": [\"item\",\"lease_type\",\"2024\",\"2023\"],\"unique_vals_per_col\": {\"item\": [\"weighted_average_remaining_lease_term\",\"weighted_average_discount_rate\"],\"lease_type\": [\"finance_leas... | 1,397 | 1 | 1 | false | false | 1 | 0 | 60 | 1 | 0 | train_all | 1 | 1 | true | true | false | [
{
"description": "Get a list of possible texts to look up for. Each text contains a singular table that is described by its complete name.",
"name": "get_descriptions",
"parameters": {
"properties": {
"company_name": {
"description": "The name of the company to get the table name... | 1 | null |
[
{
"content": "Only execute one tool call at a time. Think and reason step by step. Feel free to iteratively gather data as much as you need to answer the question. Although there is a limit of 30 turns, you can still gather data as much as you need to answer the question. When you have gathered all the data, an... | {
"content": "I have retrieved the structure of the table and now need to extract the actual data to compare lease financing strategy between 2022 and 2024. Since the table has data for 2023 and 2024, I will query the specific values to analyze changes in lease terms and discount rates.\n\n<tool_call>\n{\"name\": \"s... | [
{
"content": "Error: You are trying to query without any kind of filters, which is not allowed!",
"role": "tool"
},
{
"content": "<tool_call>\n{\"name\": \"sql_query\", \"arguments\": {\"company_name\": \"meta\", \"table_name\": \"meta_LeaseBalanceSheetInformationTableTextBlock\", \"query\": \"SELEC... | 1,239 | 1 | 0.725842 | false | false | 2 | 0 | 60 | 1 | 0 | train_all | 0.725842 | 0.725842 | true | true | false | [
{
"description": "Get a list of possible texts to look up for. Each text contains a singular table that is described by its complete name.",
"name": "get_descriptions",
"parameters": {
"properties": {
"company_name": {
"description": "The name of the company to get the table name... | 0.725842 | null |
[
{
"content": "Only execute one tool call at a time. Think and reason step by step. Feel free to iteratively gather data as much as you need to answer the question. Although there is a limit of 30 turns, you can still gather data as much as you need to answer the question. When you have gathered all the data, an... | {
"content": "The initial query failed because it was too broad. I now narrow down the query to a specific item—'weighted_average_remaining_lease_term'—to get relevant data for 2023 and 2024. This will allow me to analyze how the average lease term has changed over time, which can indicate shifts in their capital all... | [
{
"content": "[{\"item\":\"weighted_average_remaining_lease_term\",\"lease_type\":\"finance_leases\",\"2024\":\"13.7 years\",\"2023\":\"14.0 years\"},{\"item\":\"weighted_average_remaining_lease_term\",\"lease_type\":\"operating_leases\",\"2024\":\"11.5 years\",\"2023\":\"11.6 years\"}]",
"role": "tool"
}... | 1,246 | 1 | 0.990783 | false | false | 3 | 0 | 60 | 1 | 0 | train_all | 0.990783 | 0.990783 | true | true | false | [
{
"description": "Get a list of possible texts to look up for. Each text contains a singular table that is described by its complete name.",
"name": "get_descriptions",
"parameters": {
"properties": {
"company_name": {
"description": "The name of the company to get the table name... | 0.990783 | null |
[
{
"content": "Only execute one tool call at a time. Think and reason step by step. Feel free to iteratively gather data as much as you need to answer the question. Although there is a limit of 30 turns, you can still gather data as much as you need to answer the question. When you have gathered all the data, an... | {
"content": "I now need to check the weighted average discount rate for finance leases in 2023 and 2024 to understand if there's a change in the interest rate used for financing leases, which could reflect shifts in capital allocation preferences.\n\n<tool_call>\n{\"name\": \"sql_query\", \"arguments\": {\"company_n... | [
{
"content": "[{\"item\":\"weighted_average_discount_rate\",\"lease_type\":\"finance_leases\",\"2024\":\"3.6%\",\"2023\":\"3.4%\"},{\"item\":\"weighted_average_discount_rate\",\"lease_type\":\"operating_leases\",\"2024\":\"3.9%\",\"2023\":\"3.7%\"}]",
"role": "tool"
},
{
"content": "<tool_call>\n{\"... | 1,476 | 1 | 0.982746 | false | false | 4 | 0 | 60 | 1 | 0 | train_all | 0.982746 | 0.982746 | true | true | false | [
{
"description": "Get a list of possible texts to look up for. Each text contains a singular table that is described by its complete name.",
"name": "get_descriptions",
"parameters": {
"properties": {
"company_name": {
"description": "The name of the company to get the table name... | 0.982746 | null |
[
{
"content": "Only execute one tool call at a time. Think and reason step by step. Feel free to iteratively gather data as much as you need to answer the question. Although there is a limit of 30 turns, you can still gather data as much as you need to answer the question. When you have gathered all the data, an... | {
"content": "The data on discount rates suggests a slight increase in both finance and operating lease rates, but I need to verify if there are other relevant financial metrics in the lease cash flows table. This might provide further insight into capital allocation preferences.\n\n<tool_call>\n{\"name\": \"get_tabl... | [
{
"content": "{\"description\": \"supplemental_cash_flow_information_related_to_leases_is_as_follows_(in_millions):\",\"column_names\": [\"line_item\",\"2024\",\"2023\",\"2022\"],\"unique_vals_per_col\": {\"line_item\": [\"cash_paid_for_amounts_included_in_the_measurement_of_lease_liabilities:\",\"operating_cas... | 1,611 | 1 | 0.912009 | false | false | 5 | 0 | 60 | 1 | 0 | train_all | 0.912009 | 0.912009 | true | true | false | [
{
"description": "Get a list of possible texts to look up for. Each text contains a singular table that is described by its complete name.",
"name": "get_descriptions",
"parameters": {
"properties": {
"company_name": {
"description": "The name of the company to get the table name... | 0.912009 | null |
[
{
"content": "Only execute one tool call at a time. Think and reason step by step. Feel free to iteratively gather data as much as you need to answer the question. Although there is a limit of 30 turns, you can still gather data as much as you need to answer the question. When you have gathered all the data, an... | {
"content": "I now need to extract specific cash flow data related to lease liabilities to understand how Meta's cash outflows have changed over time. This will help determine if their lease financing strategy involves increasing or decreasing commitments, which reflects capital allocation preferences.\n\n<tool_call... | [
{
"content": "[{\"line_item\":\"cash_paid_for_amounts_included_in_the_measurement_of_lease_liabilities:\",\"2024\":\"\",\"2023\":\"\",\"2022\":\"\"}]",
"role": "tool"
},
{
"content": "<tool_call>\n{\"name\": \"sql_query\", \"arguments\": {\"company_name\": \"meta\", \"table_name\": \"meta_LeaseCashF... | 1,810 | 1 | 0.823759 | false | false | 6 | 0 | 60 | 1 | 0 | train_all | 0.823759 | 0.823759 | true | true | false | [
{
"description": "Get a list of possible texts to look up for. Each text contains a singular table that is described by its complete name.",
"name": "get_descriptions",
"parameters": {
"properties": {
"company_name": {
"description": "The name of the company to get the table name... | 0.823759 | null |
[
{
"content": "Only execute one tool call at a time. Think and reason step by step. Feel free to iteratively gather data as much as you need to answer the question. Although there is a limit of 30 turns, you can still gather data as much as you need to answer the question. When you have gathered all the data, an... | {
"content": "The cash flow data for lease liabilities is missing, so I will check operating cash flows for operating leases to see if there are any changes in operating lease payments. This could provide insight into how Meta manages its lease financing and capital allocation preferences.\n\n<tool_call>\n{\"name\": ... | [
{
"content": "[{\"line_item\":\"operating_cash_flows_for_operating_leases(1)\",\"2024\":\"$2,830\",\"2023\":\"$2,233\",\"2022\":\"$1,654\"}]",
"role": "tool"
},
{
"content": "<tool_call>\n{\"name\": \"sql_query\", \"arguments\": {\"company_name\": \"meta\", \"table_name\": \"meta_LeaseCashFlowsInfor... | 1,834 | 1 | 0.737414 | false | false | 7 | 0 | 60 | 1 | 0 | train_all | 0.737414 | 0.737414 | true | true | false | [
{
"description": "Get a list of possible texts to look up for. Each text contains a singular table that is described by its complete name.",
"name": "get_descriptions",
"parameters": {
"properties": {
"company_name": {
"description": "The name of the company to get the table name... | 0.737414 | null |
[
{
"content": "Only execute one tool call at a time. Think and reason step by step. Feel free to iteratively gather data as much as you need to answer the question. Although there is a limit of 30 turns, you can still gather data as much as you need to answer the question. When you have gathered all the data, an... | {
"content": "I now need to check the operating cash flows for finance leases to understand the financial impact of finance lease commitments. This will complete the picture of how Meta's lease financing strategy has evolved and what it suggests about their capital allocation preferences.\n\n<tool_call>\n{\"name\": \... | [
{
"content": "[{\"line_item\":\"operating_cash_flows_for_finance_leases\",\"2024\":\"$23\",\"2023\":\"$20\",\"2022\":\"$16\"}]",
"role": "tool"
},
{
"content": "<tool_call>\n{\"name\": \"sql_query\", \"arguments\": {\"company_name\": \"meta\", \"table_name\": \"meta_LeaseCashFlowsInformationTableTex... | 2,008 | 1 | 0.906807 | false | false | 8 | 0 | 60 | 1 | 0 | train_all | 0.906807 | 0.906807 | true | true | false | [
{
"description": "Get a list of possible texts to look up for. Each text contains a singular table that is described by its complete name.",
"name": "get_descriptions",
"parameters": {
"properties": {
"company_name": {
"description": "The name of the company to get the table name... | 0.906807 | null |
[
{
"content": "Only execute one tool call at a time. Think and reason step by step. Feel free to iteratively gather data as much as you need to answer the question. Although there is a limit of 30 turns, you can still gather data as much as you need to answer the question. When you have gathered all the data, an... | {
"content": "I now need to retrieve the financing cash flows for finance leases to understand the actual cash outflows related to finance lease obligations. This will provide a complete view of Meta's lease financing strategy and its impact on capital allocation.\n\n<tool_call>\n{\"name\": \"sql_query\", \"arguments... | [
{
"content": "[{\"line_item\":\"financing_cash_flows_for_finance_leases\",\"2024\":\"$1,969\",\"2023\":\"$1,058\",\"2022\":\"$850\"}]",
"role": "tool"
},
{
"content": "<tool_call>\n{\"name\": \"sql_query\", \"arguments\": {\"company_name\": \"meta\", \"table_name\": \"meta_LeaseCashFlowsInformationT... | 2,149 | 1 | 1 | false | false | 9 | 0 | 60 | 1 | 0 | train_all | 1 | 1 | true | true | false | [
{
"description": "Get a list of possible texts to look up for. Each text contains a singular table that is described by its complete name.",
"name": "get_descriptions",
"parameters": {
"properties": {
"company_name": {
"description": "The name of the company to get the table name... | 1 | null |
[
{
"content": "Only execute one tool call at a time. Think and reason step by step. Feel free to iteratively gather data as much as you need to answer the question. Although there is a limit of 30 turns, you can still gather data as much as you need to answer the question. When you have gathered all the data, an... | {
"content": "I now need to check the operating lease cash flows to understand the total operating lease expenses and how they have changed over time. This will help complete the analysis of Meta's lease financing strategy and capital allocation preferences.\n\n<tool_call>\n{\"name\": \"sql_query\", \"arguments\": {\... | [
{
"content": "[{\"line_item\":\"operating_leases\",\"2024\":\"$3,784\",\"2023\":\"$4,370\",\"2022\":\"$4,366\"}]",
"role": "tool"
},
{
"content": "<tool_call>\n{\"name\": \"sql_query\", \"arguments\": {\"company_name\": \"meta\", \"table_name\": \"meta_LeaseCashFlowsInformationTableTextBlock\", \"qu... | 2,306 | 1 | 0.847302 | false | false | 10 | 0 | 60 | 1 | 0 | train_all | 0.847302 | 0.847302 | true | true | false | [
{
"description": "Get a list of possible texts to look up for. Each text contains a singular table that is described by its complete name.",
"name": "get_descriptions",
"parameters": {
"properties": {
"company_name": {
"description": "The name of the company to get the table name... | 0.847302 | null |
[
{
"content": "Only execute one tool call at a time. Think and reason step by step. Feel free to iteratively gather data as much as you need to answer the question. Although there is a limit of 30 turns, you can still gather data as much as you need to answer the question. When you have gathered all the data, an... | {
"content": "I now need to retrieve the financing cash flows for finance leases to complete the analysis. This will provide the total cash outflows for finance lease obligations and allow me to compare changes over the years 2022, 2023, and 2024, which is essential to understanding the evolution of Meta's lease fina... | [
{
"content": "[{\"line_item\":\"finance_leases\",\"2024\":\"$181\",\"2023\":\"$588\",\"2022\":\"$223\"}]",
"role": "tool"
},
{
"content": "<tool_call>\n{\"name\": \"get_table_info\", \"arguments\": {\"company_name\": \"meta\", \"table_name\": \"us_gaap_LeaseCostTableTextBlock\"}}\n</tool_call>",
... | 2,444 | 1 | 0.870894 | false | false | 11 | 0 | 60 | 1 | 0 | train_all | 0.870894 | 0.870894 | true | true | false | [
{
"description": "Get a list of possible texts to look up for. Each text contains a singular table that is described by its complete name.",
"name": "get_descriptions",
"parameters": {
"properties": {
"company_name": {
"description": "The name of the company to get the table name... | 0.870894 | null |
[
{
"content": "Only execute one tool call at a time. Think and reason step by step. Feel free to iteratively gather data as much as you need to answer the question. Although there is a limit of 30 turns, you can still gather data as much as you need to answer the question. When you have gathered all the data, an... | {
"content": "The financing cash flows for finance leases show a significant decrease from 2023 to 2024, which might indicate a shift in strategy. However, to ensure accuracy, I should verify if there are any related cost tables that provide more context, such as lease costs by type. This could help clarify if the ch... | [
{
"content": "{\"description\": \"the_components_of_lease_costs_are_as_follows_(in_millions):\",\"column_names\": [\"component\",\"2024\",\"2023\",\"2022\"],\"unique_vals_per_col\": {\"component\": [\"amortization_of_right_of_use_assets\",\"interest\",\"operating_lease_cost\",\"variable_lease_cost_and_other\",\... | 2,613 | 1 | 0.359505 | false | false | 12 | 0 | 60 | 1 | 0 | train_all | 0.359505 | 0.359505 | true | true | false | [
{
"description": "Get a list of possible texts to look up for. Each text contains a singular table that is described by its complete name.",
"name": "get_descriptions",
"parameters": {
"properties": {
"company_name": {
"description": "The name of the company to get the table name... | 0.359505 | null |
[
{
"content": "Only execute one tool call at a time. Think and reason step by step. Feel free to iteratively gather data as much as you need to answer the question. Although there is a limit of 30 turns, you can still gather data as much as you need to answer the question. When you have gathered all the data, an... | {
"content": "I now have the detailed lease cost components for each year. By examining the breakdown of lease costs—such as amortization, interest, and operating lease costs—I can better understand the evolution of Meta's lease financing strategy and how capital allocation preferences have changed between 2022 and 2... | [
{
"content": "Error: You are trying to query without any kind of filters, which is not allowed!",
"role": "tool"
},
{
"content": "<tool_call>\n{\"name\": \"sql_query\", \"arguments\": {\"company_name\": \"meta\", \"table_name\": \"us_gaap_LeaseCostTableTextBlock\", \"query\": \"SELECT component, \\\... | 2,823 | 1 | 1 | false | false | 13 | 0 | 60 | 1 | 0 | train_all | 1 | 1 | true | true | false | [
{
"description": "Get a list of possible texts to look up for. Each text contains a singular table that is described by its complete name.",
"name": "get_descriptions",
"parameters": {
"properties": {
"company_name": {
"description": "The name of the company to get the table name... | 1 | null |
End of preview. Expand in Data Studio
Act-PRM Rollout Dataset
Run Metadata
- run_name:
act-prm-v2-ia=0-rr=0-ec=act_prm_finqa_reasoning_gpt5m-gc=aprm_qwen3_ap-tc=aprm_for_sft100-rbc=default-msl=4096-mc=hf_qwen3_4b_inst_2507-lc=r8_a16_qkvo-nf=0-ao=1-ho=1-eec=finqa_reasoning-gs=8-bs=8-lr=4e_05-ns=4-s=1-r=finqa_aprm_0 - run_cmd:
main_pytorch.py --env_config act_prm/finqa_reasoning_gpt5m --eval_env_config finqa/reasoning --model_config hf_qwen3_4b_inst_2507 --lora_config r8_a16_qkvo --generator_config aprm_qwen3_ap --trainer_config aprm_for_sft100 --replay_buffer_config default --log_path ./logs --actions_only --hide_observations --batch_size 8 --group_size 8 --learning_rate 4e-5 --num_substeps 4 --seed 0 --replicate finqa_aprm_0 --verbose --seed 1 --max_seq_len 4096 - batch_idx:
60 - split:
train_all - trajectory_key:
think_act_policy - num_trajectories:
508 - num_episodes:
508 - group_size:
8 - batch_size:
8
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