1sf/bird-sql-train-with-schema huggingface dataset:
Database: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: Which company falls under the category of an associated member? Please provide the organization's full name.
SQL: SELECT NAME FROM organization WHERE country IN ( SELECT country FROM politics WHERE dependent != '' )
Database: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: Which nations have a boundary with the Kalahari Desert?
Evidence: Nation refers to country
SQL: SELECT T3.Name FROM desert AS T1 INNER JOIN geo_desert AS T2 ON T1.Name = T2.Desert INNER JOIN country AS T3 ON T3.Code = T2.Country WHERE T1.Name = 'Kalahari'
Database: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: Which desert in Kazakhstan is the largest?
SQL: SELECT T1.Name FROM desert AS T1 INNER JOIN geo_desert AS T2 ON T1.Name = T2.Desert INNER JOIN country AS T3 ON T3.Code = T2.Country WHERE T3.Name = 'Kazakstan' ORDER BY T1.Area DESC LIMIT 1
Database: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: What sea does the Baltic Sea converge with, and how deep is the Baltic Sea?
Evidence: Coverage refers to mergesWith
SQL: SELECT T2.Sea2, T1.Depth FROM sea AS T1 INNER JOIN mergesWith AS T2 ON T1.Name = T2.Sea1 WHERE T1.Name = 'Baltic Sea'
Database: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: Which constitutional monarchy nations saw the greatest growth in the number of organizations after 1907?
Evidence: Nation refers to country; Information of growth appears in the column Established
SQL: SELECT T1.Name FROM country AS T1 INNER JOIN organization AS T2 ON T1.Code = T2.Country INNER JOIN politics AS T3 ON T3.Country = T2.Country WHERE STRFTIME('%Y', T2.Established) > '1907' AND T3.Government = 'constitutional monarchy' GROUP BY T1.Name ORDER BY COUNT(DISTINCT T2.Name) DESC LIMIT 1
Database: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: What kind of mountain is Ampato? Which province and nation does this mountain belong to?
Evidence: Nation refers to country
SQL: SELECT T1.Type, T3.Name, T4.Name FROM mountain AS T1 INNER JOIN geo_mountain AS T2 ON T1.Name = T2.Mountain INNER JOIN province AS T3 ON T3.Name = T2.Province INNER JOIN country AS T4 ON T3.Country = T4.Code WHERE T1.Name = 'Ampato'
Database: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: Please provide a list of every volcano mountain in the province of Ecuador.
SQL: SELECT T1.Name FROM mountain AS T1 INNER JOIN geo_mountain AS T2 ON T1.Name = T2.Mountain INNER JOIN province AS T3 ON T3.Name = T2.Province WHERE T3.Name = 'Ecuador' AND T1.Type = 'volcano'
Database: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: What percentage of nations have achieved independence since 1993 and practice parliamentary democracy? Please include any three parliament-based democracies that attained independence after 1993.
Evidence: Percentage of rivers with lengths greater than 3,000 miles = [(Total number of rivers with lengths greater than 3,000 miles) / (Total number of rivers)] * 100%
SQL: SELECT SUM(IIF(government = 'parliamentary democracy', 1, 0)) , CAST(SUM(IIF(government = 'parliamentary democracy', 1, 0)) AS REAL) * 100 / COUNT(*) FROM politics AS t1 WHERE STRFTIME('%Y', independence) >= '1993'
Database: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: What proportion of rivers have a length of more than 3,000 miles? Please provide the name of a Russian river that is more than 3,000 miles long.
Evidence: Proportion of rivers with lengths greater than 3,000 miles = [(Total number of rivers with lengths greater than 3,000 miles) / (Total number of rivers)] * 100%
SQL: SELECT CAST(SUM(CASE WHEN T1.Length > 3000 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.Name) FROM river AS T1 INNER JOIN located AS T2 ON T1.Name = T2.River INNER JOIN country AS T3 ON T3.Code = T2.Country