db_id stringclasses 11
values | instruction stringlengths 1.63k 14k | role stringclasses 45
values | policy unknown | input stringlengths 23 477 | output stringlengths 23 2.22k | difficulty stringclasses 3
values | metadata dict |
|---|---|---|---|---|---|---|---|
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | For accounts with monthly statement issuance, provide a comprehensive financial profile including client demographics, transaction activity, loan details, and rankings by transaction volume and cash flow performance. | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH MonthlyAccounts AS (\n SELECT \n account_id, \n district_id, \n date AS account_open_date\n FROM \n account \n WHERE \n frequency = 'POPLATEK MESICNE'\n),\nAccountTransactions AS (\n SELECT \n ma.account_id,\n COUNT(t.trans_id) AS transaction_count,\n SUM(CASE WHEN t.ty... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | List the top nine districts, by descending order, from the highest to the lowest, the number of female account holders. | SELECT T2.A2, COUNT(T1.client_id) FROM client AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id WHERE T1.gender = 'F' GROUP BY T2.district_id, T2.A2 ORDER BY COUNT(T1.client_id) DESC LIMIT 9 | moderate | {
"gold_sql": "SELECT T2.A2, COUNT(T1.client_id) FROM client AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id WHERE T1.gender = 'F' GROUP BY T2.district_id, T2.A2 ORDER BY COUNT(T1.client_id) DESC LIMIT 9",
"permission": "allowed",
"query_columns": {
"district": [
"A2",
"district... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | Which are the top ten withdrawals (non-credit card) by district names for the month of January 1996? | SELECT
T1.A2 AS district_name,
SUM(T3.amount) AS total_non_credit_withdrawals
FROM district AS T1
INNER JOIN account AS T2 ON T1.district_id = T2.district_id
INNER JOIN trans AS T3 ON T2.account_id = T3.account_id
WHERE
T3.type = 'VYDAJ'
AND T3.date LIKE '1996-01%'
GROUP BY T1.A2
ORDER BY tota... | moderate | {
"gold_sql": "SELECT \n T1.A2 AS district_name, \n SUM(T3.amount) AS total_non_credit_withdrawals \nFROM district AS T1\nINNER JOIN account AS T2 ON T1.district_id = T2.district_id\nINNER JOIN trans AS T3 ON T2.account_id = T3.account_id\nWHERE \n T3.type = 'VYDAJ' \n AND T3.date LIKE '1996-01%' \nGRO... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | How many of the account holders in South Bohemia still do not own credit cards? | Sorry, I cannot answer. | moderate | {
"gold_sql": "SELECT COUNT(T3.account_id) FROM district AS T1 INNER JOIN client AS T2 ON T1.district_id = T2.district_id INNER JOIN disp AS T3 ON T2.client_id = T3.client_id WHERE T1.A3 = 'south Bohemia' AND T3.type != 'OWNER'",
"permission": "denied",
"query_columns": {
"district": [
"A3",
"dist... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | Which district has highest active loan? | Sorry, I cannot answer. | moderate | {
"gold_sql": "SELECT T2.A3 FROM account AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id INNER JOIN loan AS T3 ON T1.account_id = T3.account_id WHERE T3.status IN ('C', 'D') GROUP BY T2.A3 ORDER BY SUM(T3.amount) DESC LIMIT 1",
"permission": "denied",
"query_columns": {
"district": [
... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What is the average loan amount by male borrowers? | Sorry, I cannot answer. | simple | {
"gold_sql": "SELECT AVG(T4.amount) FROM client AS T1 INNER JOIN disp AS T2 ON T1.client_id = T2.client_id INNER JOIN account AS T3 ON T2.account_id = T3.account_id INNER JOIN loan AS T4 ON T3.account_id = T4.account_id WHERE T1.gender = 'M'",
"permission": "denied",
"query_columns": {
"disp": [
"accou... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | In 1996, which districts have the highest unemployment rate? List their branch location and district name. | Sorry, I cannot answer. | simple | {
"gold_sql": "SELECT district_id, A2 FROM district WHERE A13 = (SELECT A13 FROM district ORDER BY A13 DESC LIMIT 1)",
"permission": "denied",
"query_columns": {
"district": [
"A13",
"A2",
"district_id"
]
},
"missing_columns": {
"district": [
"A13"
]
},
"reason": "M... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | For the district with the highest number of crimes in 1996, provide details including the district name, region, population, number of crimes, percentage increase in crimes from 1995 to 1996, and how many accounts were opened there. | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH CrimeStats AS (\n SELECT \n district_id,\n A16 AS crimes_1996,\n RANK() OVER (ORDER BY A16 DESC) AS crime_rank\n FROM district\n),\nAccountsByDistrict AS (\n SELECT \n a.district_id,\n COUNT(a.account_id) AS account_count,\n AVG(JULIANDAY('1996-12... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | For accounts with monthly issuance that went into negative balance after a credit card withdrawal, what are the statistics including average negative balance, maximum withdrawal amount, average number of cards per account, total gold cards, average owner age, and gender distribution of account owners? | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH AccountWithNegativeBalance AS (\n SELECT \n t.account_id,\n t.date AS transaction_date,\n t.balance,\n t.operation,\n t.amount,\n a.frequency,\n ROW_NUMBER() OVER (PARTITION BY t.account_id ORDER BY t.date DESC) AS rn\n FROM \n trans t\... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | Between 1/1/1995 and 12/31/1997, how many loans in the amount of at least 250,000 per account that chose monthly statement issuance were approved? | Sorry, I cannot answer. | moderate | {
"gold_sql": "SELECT COUNT(T1.account_id)\nFROM account AS T1\nINNER JOIN loan AS T2 ON T1.account_id = T2.account_id\nWHERE T2.date BETWEEN '1995-01-01' AND '1997-12-31'\n AND T1.frequency = 'POPLATEK MESICNE'\n AND T2.amount >= 250000;",
"permission": "denied",
"query_columns": {
"account": [
"acco... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What are the demographics and financial statistics of account owners with running loan contracts in district 1, including their average remaining debt, gender distribution, age, card ownership, transaction activity, and account balances? | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH AccountsWithRunningLoans AS (\n SELECT \n a.account_id,\n a.district_id,\n l.status,\n l.amount,\n l.duration,\n l.payments,\n (l.amount - (l.payments * l.duration)) AS remaining_debt\n FROM account AS a\n INNER JOIN loan AS l ON a.account_... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | For the district with the second-highest number of crimes committed in 1995, provide a comprehensive breakdown of all male clients including their total count, the crime count for that year, total accounts, loans, credit cards, average dispositions per client, number of clients with loans, and age distribution across y... | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH CrimeRanking AS (\n SELECT \n district_id,\n A15,\n RANK() OVER (ORDER BY A15 DESC) as crime_rank\n FROM district\n),\nSecondHighestCrimeDistrict AS (\n SELECT district_id, A15\n FROM CrimeRanking\n WHERE crime_rank = 2\n),\nClientStats AS (\n SELECT \n ... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What is the demographic and financial profile of gold credit card owners with account balances averaging over 1,000, broken down by gender? | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH gold_owner_cards AS (\n SELECT \n c.card_id,\n c.disp_id,\n c.type AS card_type,\n c.issued,\n d.account_id,\n d.client_id,\n d.type AS disp_type\n FROM card AS c\n INNER JOIN disp AS d ON c.disp_id = d.disp_id\n WHERE c.type = 'gold' AN... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What is the comprehensive financial profile of all accounts in the Pisek district, including the total number of accounts, average transactions per account, total deposits and withdrawals, average maximum balance, total credit cards issued, total loans issued, percentage of active loan amounts, and number of unique acc... | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH PisekAccounts AS (\n SELECT \n a.account_id, \n a.district_id,\n a.frequency,\n a.date,\n d.A2 AS district_name\n FROM account AS a\n INNER JOIN district AS d ON a.district_id = d.district_id\n WHERE d.A2 = 'Pisek'\n),\nAccountStats AS (\n SELECT \... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | Which districts have transactions greater than USD$10,000 in 1997? | SELECT district_id
FROM account AS T1
INNER JOIN trans AS T3 ON T1.account_id = T3.account_id
WHERE STRFTIME('%Y', T3.date) = '1997'
GROUP BY district_id
HAVING SUM(T3.amount) > 10000 | simple | {
"gold_sql": "SELECT district_id\nFROM account AS T1\nINNER JOIN trans AS T3 ON T1.account_id = T3.account_id\nWHERE STRFTIME('%Y', T3.date) = '1997'\nGROUP BY district_id\nHAVING SUM(T3.amount) > 10000",
"permission": "allowed",
"query_columns": {
"trans": [
"account_id",
"amount",
"date"
... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | Which accounts placed orders for household payment in Pisek? | SELECT DISTINCT T2.account_id FROM trans AS T1 INNER JOIN account AS T2 ON T1.account_id = T2.account_id INNER JOIN district AS T3 ON T2.district_id = T3.district_id WHERE T1.k_symbol = 'SIPO' AND T3.A2 = 'Pisek' | simple | {
"gold_sql": "SELECT DISTINCT T2.account_id FROM trans AS T1 INNER JOIN account AS T2 ON T1.account_id = T2.account_id INNER JOIN district AS T3 ON T2.district_id = T3.district_id WHERE T1.k_symbol = 'SIPO' AND T3.A2 = 'Pisek'",
"permission": "allowed",
"query_columns": {
"district": [
"A2",
"dis... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | For each account with gold credit cards, provide a comprehensive financial profile including the number of gold cards, location details, transaction history, balance statistics, loan information, and rank the accounts by their average balance. | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH GoldCardAccounts AS (\n SELECT \n T2.account_id,\n COUNT(T1.card_id) AS gold_card_count\n FROM disp AS T2 \n INNER JOIN card AS T1 ON T1.disp_id = T2.disp_id \n WHERE T1.type = 'gold'\n GROUP BY T2.account_id\n),\nAccountDetails AS (\n SELECT \n a.account_i... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What is the breakdown of credit card transaction patterns in 1998 by region, district, gender, and card type, including average transaction amounts, total spending, and how these amounts compare to district average salaries? | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH CardHolders AS (\n SELECT \n c.client_id,\n c.gender,\n d.disp_id,\n d.account_id,\n a.district_id,\n cd.type AS card_type,\n cd.issued AS card_issue_date\n FROM client c\n JOIN disp d ON c.client_id = d.client_id\n JOIN card cd ON d.dis... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | Who are the account holder identification numbers whose who have transactions on the credit card with the amount is less than the average, in 1998? | SELECT DISTINCT T1.account_id FROM trans AS T1 INNER JOIN account AS T2 ON T1.account_id = T2.account_id WHERE STRFTIME('%Y', T1.date) = '1998' AND T1.operation = 'VYBER KARTOU' AND T1.amount < (SELECT AVG(amount) FROM trans WHERE STRFTIME('%Y', date) = '1998') | moderate | {
"gold_sql": "SELECT DISTINCT T1.account_id FROM trans AS T1 INNER JOIN account AS T2 ON T1.account_id = T2.account_id WHERE STRFTIME('%Y', T1.date) = '1998' AND T1.operation = 'VYBER KARTOU' AND T1.amount < (SELECT AVG(amount) FROM trans WHERE STRFTIME('%Y', date) = '1998')",
"permission": "allowed",
"query_col... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What are the top 100 female account owners with credit cards and loans, ranked by their total loan amounts, showing their financial profile including card details, loan status, transaction statistics, savings rate, and regional loan ranking? | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH AccountOwners AS (\n SELECT \n T1.client_id,\n T1.gender,\n T1.birth_date,\n T2.account_id,\n T2.disp_id,\n T5.district_id,\n T5.frequency\n FROM client AS T1\n INNER JOIN disp AS T2 ON T1.client_id = T2.client_id\n INNER JOIN account AS... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What is the demographic and financial profile of female account owners in south Bohemia, broken down by district and age group, including their average transaction activity, net balance, loan amounts, and active loan rates? | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH ClientAccounts AS (\n SELECT \n c.client_id,\n c.gender,\n a.account_id,\n d.A3 AS region,\n d.A2 AS district_name,\n CASE \n WHEN c.birth_date > '1980-01-01' THEN 'Young'\n WHEN c.birth_date BETWEEN '1960-01-01' AND '1980-01-01' T... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | For account owners in the Tabor district, provide a comprehensive customer profile including their demographics, transaction history, loan history, credit status, and customer priority ranking based on average balance. | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH EligibleAccounts AS (\n SELECT \n T2.account_id,\n T2.district_id,\n T2.date AS account_open_date,\n T1.A2 AS district_name,\n T3.client_id\n FROM district AS T1 \n INNER JOIN account AS T2 ON T1.district_id = T2.district_id \n INNER JOIN disp AS T3 O... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | Please list the account types that are not eligible for loans, and the average income of residents in the district where the account is located exceeds $8000 but is no more than $9000. | SELECT DISTINCT T3.type FROM district AS T1 INNER JOIN account AS T2 ON T1.district_id = T2.district_id INNER JOIN disp AS T3 ON T2.account_id = T3.account_id WHERE T3.type != 'OWNER' AND T1.A11 BETWEEN 8000 AND 9000 | challenging | {
"gold_sql": "SELECT DISTINCT T3.type FROM district AS T1 INNER JOIN account AS T2 ON T1.district_id = T2.district_id INNER JOIN disp AS T3 ON T2.account_id = T3.account_id WHERE T3.type != 'OWNER' AND T1.A11 BETWEEN 8000 AND 9000",
"permission": "allowed",
"query_columns": {
"district": [
"A11",
... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | How many accounts in North Bohemia has made a transaction with the partner's bank being AB? | SELECT COUNT(T2.account_id) FROM district AS T1 INNER JOIN account AS T2 ON T1.district_id = T2.district_id INNER JOIN trans AS T3 ON T2.account_id = T3.account_id WHERE T3.bank = 'AB' AND T1.A3 = 'north Bohemia' | moderate | {
"gold_sql": "SELECT COUNT(T2.account_id) FROM district AS T1 INNER JOIN account AS T2 ON T1.district_id = T2.district_id INNER JOIN trans AS T3 ON T2.account_id = T3.account_id WHERE T3.bank = 'AB' AND T1.A3 = 'north Bohemia'",
"permission": "allowed",
"query_columns": {
"district": [
"A3",
"dis... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | For each district with withdrawal transactions, provide a comprehensive analysis including the total number and amount of withdrawals, demographic information, withdrawal per capita, and rank the districts by total withdrawal amount. Also categorize each district by unemployment level. | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH district_withdrawal_counts AS (\n SELECT \n T1.district_id,\n T1.A2 AS district_name,\n COUNT(DISTINCT T3.trans_id) AS withdrawal_count,\n SUM(T3.amount) AS total_withdrawal_amount,\n AVG(T3.amount) AS avg_withdrawal_amount\n FROM district AS T1 \n INNER... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What is the average number of crimes committed in 1995 in regions where the number exceeds 4000 and the region has accounts that are opened starting from the year 1997? | Sorry, I cannot answer. | moderate | {
"gold_sql": "SELECT AVG(sub.A15) AS avg_crimes_1995\nFROM (\n SELECT DISTINCT\n T1.district_id,\n T1.A15\n FROM district AS T1\n INNER JOIN account AS T2 ON T1.district_id = T2.district_id\n WHERE STRFTIME('%Y', T2.date) >= '1997'\n AND T1.A15 > 4000\n) AS sub;",
"permission": "denied",
"query_colu... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | For each district, how many classic credit card holders who are account owners are there, and what are their average loan amounts, account balances, loan performance, district salary, and unemployment rate? | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH loan_stats AS (\n SELECT \n l.account_id,\n COUNT(l.loan_id) AS loan_count,\n AVG(l.amount) AS avg_loan_amount,\n SUM(CASE WHEN l.status = 'A' THEN 1 ELSE 0 END) AS good_loans,\n SUM(CASE WHEN l.status = 'B' THEN 1 ELSE 0 END) AS bad_loans\n FROM loan l\n ... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What is the financial profile and banking behavior of male clients in Prague district, broken down by age groups (Young, Middle-aged, and Senior)? | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH PrahaClients AS (\n SELECT \n c.client_id,\n c.gender,\n c.birth_date,\n d.A2 AS district_name,\n CASE \n WHEN strftime('%Y', 'now') - strftime('%Y', c.birth_date) - (strftime('%m-%d', 'now') < strftime('%m-%d', c.birth_date)) < 30 THEN 'Young'\n ... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What percentage of gold credit cards were issued before 1998, both overall and broken down by region? | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH GoldCardStats AS (\n SELECT \n c.card_id,\n STRFTIME('%Y', c.issued) AS issue_year,\n d.account_id,\n CASE WHEN STRFTIME('%Y', c.issued) < '1998' THEN 1 ELSE 0 END AS is_pre_1998\n FROM card c\n JOIN disp d ON c.disp_id = d.disp_id\n WHERE c.type = 'gold'\n)... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What are the demographic, financial, and transaction details of the account owner who has the largest loan amount, including their age category, savings rate, and the economic status of their district? | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH LoanRanking AS (\n SELECT \n l.account_id,\n l.amount,\n l.loan_id,\n RANK() OVER (ORDER BY l.amount DESC) as loan_rank\n FROM loan l\n),\nAccountOwners AS (\n SELECT \n d.client_id,\n d.account_id,\n c.gender,\n c.birth_date,\n ... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | For account 532, what is the crime trend and ranking of its district, including the percentage change in crimes between 1995 and 1996, how many loans and transactions the account has, and how it compares to the average crime rate across all districts? | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH CrimesByDistrict AS (\n SELECT \n d.district_id,\n d.A2 AS district_name,\n d.A15 AS crimes_1995,\n d.A16 AS crimes_1996,\n CASE \n WHEN d.A16 > d.A15 THEN 'Increased'\n WHEN d.A16 < d.A15 THEN 'Decreased'\n ELSE 'Unchanged'\n ... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | For the account that placed order 33333, provide a comprehensive profile including the district's economic ranking by salary, account transaction history, ownership details, loan status, and order information. | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH OrderInfo AS (\n SELECT \n T1.order_id,\n T1.account_id,\n T1.amount AS order_amount,\n T1.k_symbol AS order_purpose,\n T2.district_id,\n T2.date AS account_creation_date\n FROM `order` AS T1\n INNER JOIN account AS T2 ON T1.account_id = T2.accoun... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | List all the withdrawals in cash transactions that the client with the id 3356 makes. | Sorry, I cannot answer. | simple | {
"gold_sql": "SELECT T4.trans_id FROM client AS T1 INNER JOIN disp AS T2 ON T1.client_id = T2.client_id INNER JOIN account AS T3 ON T2.account_id = T3.account_id INNER JOIN trans AS T4 ON T3.account_id = T4.account_id WHERE T1.client_id = 3356 AND T4.operation = 'VYBER'",
"permission": "denied",
"query_columns":... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | Among the weekly issuance accounts, how many have a loan of under 200000? | Sorry, I cannot answer. | simple | {
"gold_sql": "SELECT COUNT(T1.account_id)\nFROM loan AS T1\nINNER JOIN account AS T2 ON T1.account_id = T2.account_id\nWHERE T2.frequency = 'POPLATEK TYDNE' AND T1.amount < 200000;",
"permission": "denied",
"query_columns": {
"account": [
"account_id",
"frequency"
],
"loan": [
"acco... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What is the complete customer profile for client 13539, including their demographics, credit card details, district information with salary ranking, transaction activity, customer segment classification, and loan count? | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH client_account_info AS (\n SELECT\n d.client_id,\n d.account_id,\n d.disp_id,\n c.gender,\n c.birth_date,\n CAST(strftime('%Y', 'now') AS INTEGER) - CAST(strftime('%Y', c.birth_date) AS INTEGER) AS client_age,\n a.district_id,\n a.frequenc... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | For client 3541, what are the complete financial details of all their accounts including region, loan information, transaction statistics, net balance, and how many other clients are in the same region, ordered by account activity? | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH ClientRegionInfo AS (\n SELECT \n c.client_id,\n d.district_id,\n d.A2 AS district_name,\n d.A3 AS region,\n d.A11 AS avg_salary,\n d.A12 AS unemployment_rate_1995\n FROM \n client AS c\n INNER JOIN \n district AS d ON c.district_id ... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | Which district has the most accounts with loan contracts finished with no problems? | Sorry, I cannot answer. | moderate | {
"gold_sql": "SELECT T1.A2\nFROM District AS T1\nINNER JOIN Account AS T2 ON T1.District_id = T2.District_id\nINNER JOIN Loan AS T3 ON T2.Account_id = T3.Account_id\nWHERE T3.status = 'A'\nGROUP BY T1.District_id\nORDER BY COUNT(T2.Account_id) DESC\nLIMIT 1;",
"permission": "denied",
"query_columns": {
"dist... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | For order 32423, provide a comprehensive profile of the account owner including their demographics, order details, loan status, transaction history, and number of credit cards. | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH client_info AS (\n SELECT \n c.client_id,\n c.gender,\n CAST(strftime('%Y', 'now') - strftime('%Y', c.birth_date) AS INTEGER) AS age,\n d.A2 AS district_name,\n d.A3 AS region\n FROM client c\n JOIN district d ON c.district_id = d.district_id\n),\norder_details AS (\n SELECT \n ... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | Please list all the transactions made by accounts from district 5. | SELECT T3.trans_id FROM district AS T1 INNER JOIN account AS T2 ON T1.district_id = T2.district_id INNER JOIN trans AS T3 ON T2.account_id = T3.account_id WHERE T1.district_id = 5 | simple | {
"gold_sql": "SELECT T3.trans_id FROM district AS T1 INNER JOIN account AS T2 ON T1.district_id = T2.district_id INNER JOIN trans AS T3 ON T2.account_id = T3.account_id WHERE T1.district_id = 5",
"permission": "allowed",
"query_columns": {
"district": [
"district_id"
],
"trans": [
"accoun... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What is the comprehensive banking activity profile for accounts in Jesenik district, including the total number of accounts, transaction patterns, loan statistics with their repayment status, average balances, and the gender distribution of clients? | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH district_accounts AS (\n SELECT \n d.district_id,\n d.A2 AS district_name,\n a.account_id,\n a.date AS account_creation_date,\n COUNT(l.loan_id) AS loan_count,\n SUM(CASE WHEN l.status = 'A' THEN 1 ELSE 0 END) AS good_loans,\n SUM(CASE WHEN l.status = 'B' THEN 1 ELSE 0 END) A... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | List all the clients' IDs whose junior credit cards were issued after 1996. | Sorry, I cannot answer. | simple | {
"gold_sql": "SELECT T2.client_id FROM card AS T1 INNER JOIN disp AS T2 ON T1.disp_id = T2.disp_id WHERE T1.type = 'junior' AND T1.issued >= '1997-01-01'",
"permission": "denied",
"query_columns": {
"card": [
"disp_id",
"issued",
"type"
],
"disp": [
"client_id",
"disp_id... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What percentage of clients who opened their accounts in the district with an average salary of over 10000 are women? | SELECT CAST(SUM(T2.gender = 'F') AS REAL) * 100 / COUNT(T2.client_id)
FROM district AS T1
INNER JOIN client AS T2 ON T1.district_id = T2.district_id
WHERE T1.A11 > 10000; | moderate | {
"gold_sql": "SELECT CAST(SUM(T2.gender = 'F') AS REAL) * 100 / COUNT(T2.client_id)\nFROM district AS T1\nINNER JOIN client AS T2 ON T1.district_id = T2.district_id\nWHERE T1.A11 > 10000;",
"permission": "allowed",
"query_columns": {
"district": [
"A11",
"district_id"
],
"client": [
... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What was the growth rate of the total amount of loans across all accounts for a male client between 1996 and 1997? | Sorry, I cannot answer. | challenging | {
"gold_sql": "SELECT CAST((SUM(CASE WHEN STRFTIME('%Y', T1.date) = '1997' THEN T1.amount ELSE 0 END) -\n SUM(CASE WHEN STRFTIME('%Y', T1.date) = '1996' THEN T1.amount ELSE 0 END)) AS REAL) * 100 /\n SUM(CASE WHEN STRFTIME('%Y', T1.date) = '1996' THEN T1.amount ELSE 0 END)\nFROM loan AS T1\nINNER JO... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | How many credit card withdrawals were recorded after 1995? | SELECT COUNT(account_id) FROM trans WHERE STRFTIME('%Y', date) > '1995' AND operation = 'VYBER KARTOU' | simple | {
"gold_sql": "SELECT COUNT(account_id) FROM trans WHERE STRFTIME('%Y', date) > '1995' AND operation = 'VYBER KARTOU'",
"permission": "allowed",
"query_columns": {
"trans": [
"account_id"
]
},
"missing_columns": {},
"reason": "All required columns are permitted",
"question_id": 170,
"evide... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What was the difference in the number of crimes committed in East and North Bohemia in 1996? | SELECT SUM(IIF(A3 = 'north Bohemia', A16, 0)) - SUM(IIF(A3 = 'east Bohemia', A16, 0)) FROM district | moderate | {
"gold_sql": "SELECT SUM(IIF(A3 = 'north Bohemia', A16, 0)) - SUM(IIF(A3 = 'east Bohemia', A16, 0)) FROM district",
"permission": "allowed",
"query_columns": {
"district": [
"A16",
"A3"
]
},
"missing_columns": {},
"reason": "All required columns are permitted",
"question_id": 171,
"... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | How many owner and disponent dispositions are there from account number 1 to account number 10? | SELECT SUM(type = 'OWNER') , SUM(type = 'DISPONENT') FROM disp WHERE account_id BETWEEN 1 AND 10 | simple | {
"gold_sql": "SELECT SUM(type = 'OWNER') , SUM(type = 'DISPONENT') FROM disp WHERE account_id BETWEEN 1 AND 10",
"permission": "allowed",
"query_columns": {
"disp": [
"account_id"
]
},
"missing_columns": {},
"reason": "All required columns are permitted",
"question_id": 172,
"evidence": "... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | How often does account number 3 request an account statement to be released? What was the aim of debiting 3539 in total? | Sorry, I cannot answer. | challenging | {
"gold_sql": "SELECT T1.frequency, T2.k_symbol FROM account AS T1 INNER JOIN (SELECT account_id, k_symbol, SUM(amount) AS total_amount FROM `order` GROUP BY account_id, k_symbol) AS T2 ON T1.account_id = T2.account_id WHERE T1.account_id = 3 AND T2.total_amount = 3539",
"permission": "denied",
"query_columns": {... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What year was account owner number 130 born? | Sorry, I cannot answer. | simple | {
"gold_sql": "SELECT STRFTIME('%Y', T1.birth_date) FROM client AS T1 INNER JOIN disp AS T3 ON T1.client_id = T3.client_id INNER JOIN account AS T2 ON T3.account_id = T2.account_id WHERE T2.account_id = 130",
"permission": "denied",
"query_columns": {
"disp": [
"account_id",
"client_id"
],
... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | For accounts with owner disposition that request statements after each transaction, what are the regional and district-level statistics including the number of accounts, average district salary, loan adoption rate, average loan amount, transaction activity, and account balances? | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH owner_accounts AS (\n SELECT DISTINCT a.account_id, a.district_id, a.frequency, a.date\n FROM account a\n JOIN disp d ON a.account_id = d.account_id\n WHERE d.type = 'OWNER' AND a.frequency = 'POPLATEK PO OBRATU'\n),\ndistrict_stats AS (\n SELECT \n d.district_id,\n d.... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What is the amount of debt that client number 992 has, and how is this client doing with payments? | Sorry, I cannot answer. | simple | {
"gold_sql": "SELECT T4.amount, T4.status FROM client AS T1 INNER JOIN disp AS T2 ON T1.client_id = T2.client_id INNER JOIN account AS T3 on T2.account_id = T3.account_id INNER JOIN loan AS T4 ON T3.account_id = T4.account_id WHERE T1.client_id = 992",
"permission": "denied",
"query_columns": {
"disp": [
... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What is the sum that client number 4's account has following transaction 851? Who owns this account, a man or a woman? | Sorry, I cannot answer. | simple | {
"gold_sql": "SELECT T4.balance, T1.gender FROM client AS T1 INNER JOIN disp AS T2 ON T1.client_id = T2.client_id INNER JOIN account AS T3 ON T2.account_id =T3.account_id INNER JOIN trans AS T4 ON T3.account_id = T4.account_id WHERE T1.client_id = 4 AND T4.trans_id = 851",
"permission": "denied",
"query_columns"... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What are the complete details of client number 9 including their gender, birth date, credit card type, when the card was issued, customer status, total number of accounts owned, and how long they've had their most recent card? | Sorry, I cannot answer. | challenging | {
"gold_sql": "SELECT \n cl.client_id,\n cl.gender,\n DATE(cl.birth_date) AS birth_date,\n cd.type AS card_type,\n DATE(cd.issued) AS card_issued_date,\n CASE \n WHEN cd.type = 'gold' THEN 'Premium Customer'\n WHEN cd.type = 'classic' THEN 'Regular Customer'\n ELSE 'Other Custom... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | How much, in total, did client number 617 pay for all of the transactions in 1998? | Sorry, I cannot answer. | simple | {
"gold_sql": "SELECT SUM(T2.amount) FROM disp AS T1 INNER JOIN trans AS T2 ON T2.account_id = T1.account_id WHERE STRFTIME('%Y', T2.date) = '1998' AND T1.client_id = 617",
"permission": "denied",
"query_columns": {
"trans": [
"account_id",
"amount",
"date"
],
"disp": [
"accoun... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | Please provide a list of clients who were born between 1983 and 1987 and whose account branch is in East Bohemia, along with their IDs. | Sorry, I cannot answer. | moderate | {
"gold_sql": "SELECT T1.client_id, T3.account_id\nFROM client AS T1\nINNER JOIN district AS T2 ON T1.district_id = T2.district_id\nINNER JOIN disp AS T4 ON T1.client_id = T4.client_id\nINNER JOIN account AS T3 ON T2.district_id = T3.district_id AND T4.account_id = T3.account_id\nWHERE T2.A3 = 'east Bohemia' AND STRF... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | For the top 3 female clients with the largest loans, what are their loan details including total payments, interest paid, loan status, location, transaction activity, income category, and age? | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH client_loans AS (\n SELECT \n c.client_id,\n c.gender,\n d.account_id,\n l.loan_id,\n l.amount,\n l.duration,\n l.payments,\n l.status,\n a.district_id,\n di.A2 AS district_name,\n di.A3 AS region,\n RANK() OVER... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | How many male customers who were born between 1974 and 1976 have made a payment on their home in excess of $4000? | Sorry, I cannot answer. | moderate | {
"gold_sql": "SELECT COUNT(T1.account_id) FROM trans AS T1 INNER JOIN account AS T2 ON T1.account_id = T2.account_id INNER JOIN disp AS T4 ON T2.account_id = T4.account_id INNER JOIN client AS T3 ON T4.client_id = T3.client_id WHERE STRFTIME('%Y', T3.birth_date) BETWEEN '1974' AND '1976' AND T3.gender = 'M' AND T1.a... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | For accounts opened in Beroun after 1996, what are the yearly statistics including account owner demographics, transaction volumes, loan performance, and credit card distribution? | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH AccountsInBeroun AS (\n SELECT \n a.account_id,\n a.date,\n d.A2 AS district_name,\n STRFTIME('%Y', a.date) AS opening_year,\n a.frequency\n FROM \n account AS a\n INNER JOIN \n district AS d ON a.district_id = d.district_id\n WHERE \n ... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | How many female customers have a junior credit card? | Sorry, I cannot answer. | simple | {
"gold_sql": "SELECT COUNT(T1.client_id) FROM client AS T1 INNER JOIN disp AS T2 ON T1.client_id = T2.client_id INNER JOIN card AS T3 ON T2.disp_id = T3.disp_id WHERE T1.gender = 'F' AND T3.type = 'junior'",
"permission": "denied",
"query_columns": {
"card": [
"disp_id",
"type"
],
"disp":... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What proportion of customers who have accounts at the Prague branch are female? | SELECT CAST(SUM(T2.gender = 'F') AS REAL) / COUNT(T2.client_id) * 100
FROM district AS T1
INNER JOIN client AS T2 ON T1.district_id = T2.district_id
WHERE T1.A3 = 'Prague'; | moderate | {
"gold_sql": "SELECT CAST(SUM(T2.gender = 'F') AS REAL) / COUNT(T2.client_id) * 100\nFROM district AS T1\nINNER JOIN client AS T2 ON T1.district_id = T2.district_id\nWHERE T1.A3 = 'Prague';",
"permission": "allowed",
"query_columns": {
"district": [
"A3",
"district_id"
],
"client": [
... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What percentage of male clients request for weekly statements to be issued? | Sorry, I cannot answer. | moderate | {
"gold_sql": "SELECT CAST(SUM(T1.gender = 'M') AS REAL) * 100 / COUNT(T1.client_id) FROM client AS T1 INNER JOIN account AS T2 ON T2.district_id = T1.district_id INNER JOIN disp as T3 on T1.client_id = T3.client_id AND T2.account_id = T3.account_id WHERE T2.frequency = 'POPLATEK TYDNE'",
"permission": "denied",
... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What are the key statistics for account owners with weekly statement issuance, including how many owners there are, their average number of transactions, how many have credit cards, how many are high-volume clients with over 10,000 in total transactions, the number of districts they're located in, and their average acc... | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH ClientTransactionStats AS (\n SELECT \n T2.client_id,\n COUNT(DISTINCT T3.trans_id) AS transaction_count,\n SUM(T3.amount) AS total_transaction_amount,\n AVG(T3.balance) AS avg_balance\n FROM account AS T1\n JOIN disp AS T2 ON T2.account_id = T1.account_id\n ... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | For accounts with loans exceeding 24 months duration that were opened before 1997, provide comprehensive details about the account(s) with the smallest loan amount, including transaction history, card information, client demographics, and order activity. | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH AccountsWithLongLoans AS (\n SELECT \n l.account_id,\n l.amount,\n l.duration,\n a.date AS account_opening_date,\n STRFTIME('%Y', a.date) AS opening_year,\n d.district_id,\n d.A2 AS district_name,\n d.A3 AS region\n FROM \n loan ... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | Name the account numbers of female clients who are oldest and have lowest average salary? | Sorry, I cannot answer. | moderate | {
"gold_sql": "SELECT T3.account_id\nFROM client AS T1\nINNER JOIN district AS T2 ON T1.district_id = T2.district_id\nINNER JOIN account AS T3 ON T2.district_id = T3.district_id\nINNER JOIN disp AS T4 ON T1.client_id = T4.client_id AND T4.account_id = T3.account_id\nWHERE T1.gender = 'F'\nORDER BY T1.birth_date ASC, ... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What are the comprehensive statistics for clients born in 1920 who live in east Bohemia, including their account activity, loan information, transaction patterns, gender distribution, and most common district? | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH ClientsInEastBohemia AS (\n SELECT \n c.client_id,\n c.birth_date,\n c.gender,\n d.A2 AS district_name,\n d.A3 AS region,\n STRFTIME('%Y', c.birth_date) AS birth_year,\n COUNT(DISTINCT a.account_id) AS num_accounts,\n COUNT(DISTINCT l.loan... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What are the statistics for the top 50 highest loan amounts among 24-month loans with weekly statement issuance that have an owner, including total count, average loan amount, payment details, interest rates, loan status distribution, and district economic indicators? | Sorry, I cannot answer. | challenging | {
"gold_sql": "WITH LoanAccountStats AS (\n SELECT \n a.account_id,\n a.district_id,\n a.frequency,\n l.duration,\n l.amount,\n l.payments,\n l.status,\n d.A2 AS district_name,\n d.A3 AS region,\n d.A11 AS avg_salary,\n d.A12 AS unemploym... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | What is the average amount of loan which are still on running contract with statement issuance after each transaction? | Sorry, I cannot answer. | moderate | {
"gold_sql": "SELECT AVG(T2.amount) FROM account AS T1 INNER JOIN loan AS T2 ON T1.account_id = T2.account_id WHERE T2.status IN ('C', 'D') AND T1.frequency = 'POPLATEK PO OBRATU'",
"permission": "denied",
"query_columns": {
"account": [
"account_id",
"frequency"
],
"loan": [
"accou... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | List all ID and district for clients that can only have the right to issue permanent orders or apply for loans. | Sorry, I cannot answer. | moderate | {
"gold_sql": "SELECT T3.client_id, T2.district_id, T2.A2 FROM account AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id INNER JOIN disp AS T3 ON T1.account_id = T3.account_id WHERE T3.type = 'OWNER'",
"permission": "denied",
"query_columns": {
"district": [
"A2",
"district_id"
... |
financial | ##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Database: financial
Total Tables: 8
Total Columns: 55
Table Schemas:
Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text):... | DataOperator_3 | {
"account": [
"account_id",
"date",
"district_id"
],
"card": [
"disp_id",
"issued",
"type"
],
"client": [
"*"
],
"disp": [
"account_id",
"type"
],
"district": [
"A10",
"A11",
"A14",
"A16",
"A2",
"A3",
"A4",
"A5",
"A6",
"A7",
... | Provide the IDs and age of the client with high level credit card, which is eligible for loans. | Sorry, I cannot answer. | moderate | {
"gold_sql": "SELECT T1.client_id, STRFTIME('%Y', CURRENT_TIMESTAMP) - STRFTIME('%Y', T3.birth_date) FROM disp AS T1 INNER JOIN card AS T2 ON T2.disp_id = T1.disp_id INNER JOIN client AS T3 ON T1.client_id = T3.client_id WHERE T2.type = 'gold' AND T1.type = 'OWNER'",
"permission": "denied",
"query_columns": {
... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | Which are the cards that have incredibly powerful foils. | SELECT id FROM cards WHERE cardKingdomFoilId IS NOT NULL AND cardKingdomId IS NOT NULL | simple | {
"gold_sql": "SELECT id FROM cards WHERE cardKingdomFoilId IS NOT NULL AND cardKingdomId IS NOT NULL",
"permission": "allowed",
"query_columns": {
"cards": [
"cardKingdomFoilId",
"cardKingdomId",
"id"
]
},
"missing_columns": {},
"reason": "All required columns are permitted",
"q... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | What are the borderless cards available without powerful foils? | SELECT id FROM cards WHERE borderColor = 'borderless' AND (cardKingdomFoilId IS NULL OR cardKingdomId IS NULL) | simple | {
"gold_sql": "SELECT id FROM cards WHERE borderColor = 'borderless' AND (cardKingdomFoilId IS NULL OR cardKingdomId IS NULL)",
"permission": "allowed",
"query_columns": {
"cards": [
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"id"
]
},
"missing_columns": {},
"reason... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | List the card names with value that cost more converted mana. | SELECT DISTINCT name FROM cards WHERE ConvertedManaCost = (SELECT MAX(ConvertedManaCost) FROM cards) | simple | {
"gold_sql": "SELECT DISTINCT name FROM cards WHERE ConvertedManaCost = (SELECT MAX(ConvertedManaCost) FROM cards)",
"permission": "allowed",
"query_columns": {
"cards": [
"convertedManaCost",
"name"
]
},
"missing_columns": {},
"reason": "All required columns are permitted",
"question... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | Name all cards with 2015 frame style ranking below 100 on EDHRec. | Sorry, I cannot answer. | simple | {
"gold_sql": "SELECT id FROM cards WHERE edhrecRank < 100 AND frameVersion = 2015",
"permission": "denied",
"query_columns": {
"cards": [
"edhrecRank",
"frameVersion",
"id"
]
},
"missing_columns": {
"cards": [
"frameVersion"
]
},
"reason": "Missing column permissio... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | List all the mythic rarity print cards banned in gladiator format. | Sorry, I cannot answer. | moderate | {
"gold_sql": "SELECT DISTINCT T1.id FROM cards AS T1 INNER JOIN legalities AS T2 ON T1.uuid = T2.uuid WHERE T2.format = 'gladiator' AND T2.status = 'Banned' AND T1.rarity = 'mythic'",
"permission": "denied",
"query_columns": {
"legalities": [
"format",
"status",
"uuid"
],
"cards": [... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | For artifact type of cards that do not have multiple faces on the same card, state its legalities status for vintage play format. | SELECT DISTINCT T2.status FROM cards AS T1 INNER JOIN legalities AS T2 ON T1.uuid = T2.uuid WHERE T1.type = 'Artifact' AND T2.format = 'vintage' AND T1.side IS NULL | moderate | {
"gold_sql": "SELECT DISTINCT T2.status FROM cards AS T1 INNER JOIN legalities AS T2 ON T1.uuid = T2.uuid WHERE T1.type = 'Artifact' AND T2.format = 'vintage' AND T1.side IS NULL",
"permission": "allowed",
"query_columns": {
"legalities": [
"format",
"status",
"uuid"
],
"cards": [
... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | List all the card id and artist with unknown power which are legal for commander play format. | Sorry, I cannot answer. | moderate | {
"gold_sql": "SELECT T1.id, T1.artist FROM cards AS T1 INNER JOIN legalities AS T2 ON T1.uuid = T2.uuid WHERE T2.status = 'Legal' AND T2.format = 'commander' AND (T1.power IS NULL OR T1.power = '*')",
"permission": "denied",
"query_columns": {
"legalities": [
"format",
"status",
"uuid"
... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | Find all cards illustrated by Stephen Daniel and describe the text of the ruling of these cards. State if these cards have missing or degraded properties and values. | Sorry, I cannot answer. | moderate | {
"gold_sql": "SELECT T1.id, T2.text, T1.hasContentWarning FROM cards AS T1 INNER JOIN rulings AS T2 ON T1.uuid = T2.uuid WHERE T1.artist = 'Stephen Daniele'",
"permission": "denied",
"query_columns": {
"cards": [
"artist",
"hasContentWarning",
"id",
"uuid"
],
"rulings": [
... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | Describe the information about rulings for card named 'Sublime Epiphany' with number 74s. | SELECT T2.text FROM cards AS T1 INNER JOIN rulings AS T2 ON T1.uuid = T2.uuid WHERE T1.name = 'Sublime Epiphany' AND T1.number = '74s' | simple | {
"gold_sql": "SELECT T2.text FROM cards AS T1 INNER JOIN rulings AS T2 ON T1.uuid = T2.uuid WHERE T1.name = 'Sublime Epiphany' AND T1.number = '74s'",
"permission": "allowed",
"query_columns": {
"cards": [
"name",
"number",
"uuid"
],
"rulings": [
"text",
"uuid"
]
}... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | Name the card and artist with the most ruling information. Also state if the card is a promotional printing. | Sorry, I cannot answer. | moderate | {
"gold_sql": "SELECT\n T1.name,\n T1.artist,\n CASE WHEN T1.isPromo = 1 THEN 'yes' ELSE 'no' END AS isPromo\nFROM cards AS T1\nJOIN rulings AS T2 ON T2.uuid = T1.uuid\nGROUP BY T1.uuid, T1.name, T1.artist, T1.isPromo\nORDER BY COUNT(T2.uuid) DESC, T1.uuid ASC\nLIMIT 1;",
"permission": "denied",
"query_columns... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | State the alternative languages available for card named Annul numbered 29. | SELECT T2.language FROM cards AS T1 INNER JOIN foreign_data AS T2 ON T1.uuid = T2.uuid WHERE T1.name = 'Annul' AND T1.number = '29' | simple | {
"gold_sql": "SELECT T2.language FROM cards AS T1 INNER JOIN foreign_data AS T2 ON T1.uuid = T2.uuid WHERE T1.name = 'Annul' AND T1.number = '29'",
"permission": "allowed",
"query_columns": {
"foreign_data": [
"language",
"uuid"
],
"cards": [
"name",
"number",
"uuid"
... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | Name all the cards which have alternative language in Japanese. | SELECT DISTINCT T1.name FROM cards AS T1 INNER JOIN foreign_data AS T2 ON T1.uuid = T2.uuid WHERE T2.language = 'Japanese' | simple | {
"gold_sql": "SELECT DISTINCT T1.name FROM cards AS T1 INNER JOIN foreign_data AS T2 ON T1.uuid = T2.uuid WHERE T2.language = 'Japanese'",
"permission": "allowed",
"query_columns": {
"foreign_data": [
"language",
"uuid"
],
"cards": [
"name",
"uuid"
]
},
"missing_column... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | Calculate the percentage of the cards availabe in Chinese Simplified. | SELECT CAST(SUM(CASE WHEN T2.language = 'Chinese Simplified' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.id) FROM cards AS T1 INNER JOIN foreign_data AS T2 ON T1.uuid = T2.uuid | moderate | {
"gold_sql": "SELECT CAST(SUM(CASE WHEN T2.language = 'Chinese Simplified' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.id) FROM cards AS T1 INNER JOIN foreign_data AS T2 ON T1.uuid = T2.uuid",
"permission": "allowed",
"query_columns": {
"foreign_data": [
"language",
"uuid"
],
"cards": [
... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | List all the sets available in Italian translation. State the total number of cards per set. | Sorry, I cannot answer. | simple | {
"gold_sql": "SELECT T1.name, T1.totalSetSize FROM sets AS T1 INNER JOIN set_translations AS T2 ON T1.code = T2.setCode WHERE T2.language = 'Italian'",
"permission": "denied",
"query_columns": {
"sets": [
"code",
"name",
"totalSetSize"
],
"set_translations": [
"language",
... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | How many types of cards does the artist Aaron Boyd illustrated about card art? | Sorry, I cannot answer. | simple | {
"gold_sql": "SELECT COUNT(type) FROM cards WHERE artist = 'Aaron Boyd'",
"permission": "denied",
"query_columns": {
"cards": [
"artist"
]
},
"missing_columns": {
"cards": [
"artist"
]
},
"reason": "Missing column permissions: cards: artist",
"question_id": 354,
"evidence"... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | What is the keyword found on card 'Angel of Mercy'? | SELECT DISTINCT keywords FROM cards WHERE name = 'Angel of Mercy' | simple | {
"gold_sql": "SELECT DISTINCT keywords FROM cards WHERE name = 'Angel of Mercy'",
"permission": "allowed",
"query_columns": {
"cards": [
"keywords",
"name"
]
},
"missing_columns": {},
"reason": "All required columns are permitted",
"question_id": 355,
"evidence": "Angel of Mercy' is... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | How many cards have infinite power? | SELECT COUNT(*) FROM cards WHERE power = '*' | simple | {
"gold_sql": "SELECT COUNT(*) FROM cards WHERE power = '*'",
"permission": "allowed",
"query_columns": {
"cards": [
"power"
]
},
"missing_columns": {},
"reason": "All required columns are permitted",
"question_id": 356,
"evidence": "infinite power refers to power = '*';"
} |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | What type of promotion is of card 'Duress'? | SELECT DISTINCT promoTypes
FROM cards
WHERE name = 'Duress' AND promoTypes IS NOT NULL | simple | {
"gold_sql": "SELECT DISTINCT promoTypes \nFROM cards \nWHERE name = 'Duress' AND promoTypes IS NOT NULL",
"permission": "allowed",
"query_columns": {
"cards": [
"name",
"promoTypes"
]
},
"missing_columns": {},
"reason": "All required columns are permitted",
"question_id": 357,
"evi... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | What is the border color of card "Ancestor's Chosen"? | SELECT DISTINCT borderColor FROM cards WHERE name = 'Ancestor''s Chosen' | simple | {
"gold_sql": "SELECT DISTINCT borderColor FROM cards WHERE name = 'Ancestor''s Chosen'",
"permission": "allowed",
"query_columns": {
"cards": [
"borderColor",
"name"
]
},
"missing_columns": {},
"reason": "All required columns are permitted",
"question_id": 358,
"evidence": "name of ... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | What is the type of the card "Ancestor's Chosen" as originally printed? | Sorry, I cannot answer. | simple | {
"gold_sql": "SELECT originalType FROM cards WHERE name = \"Ancestor's Chosen\" AND originalType IS NOT NULL",
"permission": "denied",
"query_columns": {
"cards": [
"name",
"originalType"
]
},
"missing_columns": {
"cards": [
"originalType"
]
},
"reason": "Missing column ... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | What are the languages available for the set that card 'Angel of Mercy' is in? | SELECT DISTINCT
s.`language`
FROM cards AS c
JOIN set_translations AS s ON s.setCode = c.setCode
WHERE c.name = 'Angel of Mercy' | moderate | {
"gold_sql": "SELECT DISTINCT\n s.`language`\nFROM cards AS c\nJOIN set_translations AS s ON s.setCode = c.setCode\nWHERE c.name = 'Angel of Mercy'",
"permission": "allowed",
"query_columns": {
"cards": [
"name",
"setCode"
],
"set_translations": [
"language",
"setCode"
]
... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | How many cards of legalities whose status is restricted have text boxes? | Sorry, I cannot answer. | simple | {
"gold_sql": "SELECT COUNT(DISTINCT T1.id) FROM cards AS T1 INNER JOIN legalities AS T2 ON T1.uuid = T2.uuid WHERE T2.status = 'Restricted' AND T1.isTextless = 0",
"permission": "denied",
"query_columns": {
"legalities": [
"status",
"uuid"
],
"cards": [
"id",
"isTextless",
... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | What is the description about the ruling of card "Condemn"? | SELECT T2.text FROM cards AS T1 INNER JOIN rulings AS T2 ON T1.uuid = T2.uuid WHERE T1.name = 'Condemn' | simple | {
"gold_sql": "SELECT T2.text FROM cards AS T1 INNER JOIN rulings AS T2 ON T1.uuid = T2.uuid WHERE T1.name = 'Condemn'",
"permission": "allowed",
"query_columns": {
"cards": [
"name",
"uuid"
],
"rulings": [
"text",
"uuid"
]
},
"missing_columns": {},
"reason": "All req... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | How many cards of legalities whose status is restricted are found in a starter deck? | SELECT COUNT(T1.id)
FROM cards AS T1
INNER JOIN legalities AS T2 ON T1.uuid = T2.uuid
WHERE T2.status = 'Restricted' AND T1.isStarter = 1 | simple | {
"gold_sql": "SELECT COUNT(T1.id) \nFROM cards AS T1 \nINNER JOIN legalities AS T2 ON T1.uuid = T2.uuid \nWHERE T2.status = 'Restricted' AND T1.isStarter = 1",
"permission": "allowed",
"query_columns": {
"legalities": [
"status",
"uuid"
],
"cards": [
"id",
"isStarter",
"... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | What is the status of card "Cloudchaser Eagle"? | SELECT DISTINCT T2.status FROM cards AS T1 INNER JOIN legalities AS T2 ON T1.uuid = T2.uuid WHERE T1.name = 'Cloudchaser Eagle' | simple | {
"gold_sql": "SELECT DISTINCT T2.status FROM cards AS T1 INNER JOIN legalities AS T2 ON T1.uuid = T2.uuid WHERE T1.name = 'Cloudchaser Eagle'",
"permission": "allowed",
"query_columns": {
"legalities": [
"status",
"uuid"
],
"cards": [
"name",
"uuid"
]
},
"missing_colum... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | What is the type of card "Benalish Knight"? | SELECT type
FROM cards
WHERE name = 'Benalish Knight'; | simple | {
"gold_sql": "SELECT type \nFROM cards \nWHERE name = 'Benalish Knight';",
"permission": "allowed",
"query_columns": {
"cards": [
"name"
]
},
"missing_columns": {},
"reason": "All required columns are permitted",
"question_id": 365,
"evidence": "Benalish Knight' is the name of card;"
} |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | What is the rule of playing card "Benalish Knight"? | SELECT T2.format FROM cards AS T1 INNER JOIN legalities AS T2 ON T1.uuid = T2.uuid WHERE T1.name = 'Benalish Knight' | simple | {
"gold_sql": "SELECT T2.format FROM cards AS T1 INNER JOIN legalities AS T2 ON T1.uuid = T2.uuid WHERE T1.name = 'Benalish Knight'",
"permission": "allowed",
"query_columns": {
"legalities": [
"format",
"uuid"
],
"cards": [
"name",
"uuid"
]
},
"missing_columns": {},
... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | Please provide the names of the artists who illustrated the card art in Phyrexian. | Sorry, I cannot answer. | simple | {
"gold_sql": "SELECT T1.artist FROM cards AS T1 INNER JOIN foreign_data AS T2 ON T1.uuid = T2.uuid WHERE T2.language = 'Phyrexian'",
"permission": "denied",
"query_columns": {
"foreign_data": [
"language",
"uuid"
],
"cards": [
"artist",
"uuid"
]
},
"missing_columns": {... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | What is the percentage of borderless cards? | SELECT CAST(SUM(CASE WHEN borderColor = 'borderless' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(id) FROM cards | simple | {
"gold_sql": "SELECT CAST(SUM(CASE WHEN borderColor = 'borderless' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(id) FROM cards",
"permission": "allowed",
"query_columns": {
"cards": [
"borderColor",
"id"
]
},
"missing_columns": {},
"reason": "All required columns are permitted",
"questio... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | How many cards that illusrtated in German have been reprinted? | SELECT COUNT(T1.id) FROM cards AS T1 INNER JOIN foreign_data AS T2 ON T1.uuid = T2.uuid WHERE T2.language = 'German' AND T1.isReprint = 1 | simple | {
"gold_sql": "SELECT COUNT(T1.id) FROM cards AS T1 INNER JOIN foreign_data AS T2 ON T1.uuid = T2.uuid WHERE T2.language = 'German' AND T1.isReprint = 1",
"permission": "allowed",
"query_columns": {
"foreign_data": [
"language",
"uuid"
],
"cards": [
"id",
"isReprint",
"uu... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | How many borderless cards are illustrated in Russian? | SELECT COUNT(T1.id) FROM cards AS T1 INNER JOIN foreign_data AS T2 ON T1.uuid = T2.uuid WHERE T1.borderColor = 'borderless' AND T2.language = 'Russian' | simple | {
"gold_sql": "SELECT COUNT(T1.id) FROM cards AS T1 INNER JOIN foreign_data AS T2 ON T1.uuid = T2.uuid WHERE T1.borderColor = 'borderless' AND T2.language = 'Russian'",
"permission": "allowed",
"query_columns": {
"foreign_data": [
"language",
"uuid"
],
"cards": [
"borderColor",
... |
card_games | ##Instruction:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Database: card_games
Total Tables: 6
Total Columns: 115
Table Schemas:
Table: cards (74 columns)
-------------------------
• id (integer)
• artist (text): The name of the artist that illustrated the card art.
• asciiName (text): T... | DataOperator_1 | {
"cards": [
"asciiName",
"availability",
"borderColor",
"cardKingdomFoilId",
"cardKingdomId",
"colorIdentity",
"colors",
"convertedManaCost",
"duelDeck",
"edhrecRank",
"faceConvertedManaCost",
"faceName",
"flavorText",
"frameEffects",
"hasAlternativeDeckLim... | What is the percentage of cards whose language is French among the Story Spotlight cards? | Sorry, I cannot answer. | challenging | {
"gold_sql": "SELECT CAST(SUM(CASE WHEN T2.language = 'French' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.id) FROM cards AS T1 INNER JOIN foreign_data AS T2 ON T1.uuid = T2.uuid WHERE T1.isStorySpotlight = 1",
"permission": "denied",
"query_columns": {
"foreign_data": [
"language",
"uuid"
]... |
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