You are given the conttent of a table in the input (row by row). Generate an unambiguous question based on the information present in the table, such that: 1) It's answer is unique and is in the given table, 2) Its answer is a contiguous text span from the table. Avoid creating questions that can be answered correctly without reading/understanding the table

Example Input: Table: ['Pos.', 'City', 'Population (ab)', 'Surface (km2)', 'Density (ab/km2)', 'Altitude (mslm)']. ['1st', 'Bergamo', '121.316', '39,6', '3064', '249']. ['2nd', 'Treviglio', '29.334', '31,54', '930', '125']. ['3rd', 'Seriate', '25.036', '12,41', '2017', '247']. ['4th', 'Dalmine', '23.237', '11,6', '2003', '207']. ['5th', 'Romano di Lombardia', '19.472', '18,03', '1080', '120']. ['6th', 'Albino', '18.232', '31,32', '582', '342']. ['7th', 'Caravaggio', '16.258', '32,81', '496', '111']. ['8th', 'Alzano Lombardo', '13.821', '13,43', '1029', '304']. ['9th', 'Stezzano', '12.999', '9,25', '1405', '211']. ['10th', 'Osio Sotto', '12.083', '7,45', '1622', '182']
Example Output: what are all the cities?

Example Input: Table: ['Rank', 'Player', 'County', 'Tally', 'Total', 'Opposition']. ['1', 'Nicky English', 'Tipperary', '2-12', '18', 'Antrim']. ['2', 'Mark Corrigan', 'Offaly', '3-7', '16', 'Kilkenny']. ['3', 'Joe Hennessy', 'Kerry', '3-5', '14', 'Limerick']. ['3', 'Finbarr Delaney', 'Cork', '1-11', '14', 'Waterford']. ['5', 'Nicky English', 'Tipperary', '0-13', '13', 'Waterford']. ['5', 'Adrian Ronan', 'Kilkenny', '1-10', '13', 'Westmeath']. ['7', 'Nicky English', 'Tipperary', '2-5', '11', 'Limerick']. ['7', 'Danny McNaughton', 'Antrim', '2-5', '11', 'Down']. ['9', 'M. J. Ryan', 'Dublin', '1-7', '10', 'Laois']. ['10', 'Gary Kirby', 'Limerick', '1-6', '9', 'Kerry']. ['10', 'Pat Murphy', 'Waterford', '3-0', '9', 'Cork']
Example Output: which of the following players were ranked in the bottom 5?

Example Input: Table: ['Pos', 'No', 'Rider', 'Manufacturer', 'Laps', 'Time', 'Grid', 'Points']. ['1', '58', 'Marco Simoncelli', 'Gilera', '25', '39:02.553', '1', '25']. ['2', '19', 'Alvaro Bautista', 'Aprilia', '25', '+0.223', '3', '20']. ['3', '36', 'Mika Kallio', 'KTM', '25', '+14.450', '2', '16']. ['4', '60', 'Julian Simon', 'KTM', '25', '+14.478', '6', '13']. ['5', '6', 'Alex Debon', 'Aprilia', '25', '+26.226', '8', '11']. ['6', '15', 'Roberto Locatelli', 'Gilera', '25', '+26.392', '11', '10']. ['7', '72', 'Yuki Takahashi', 'Honda', '25', '+26.434', '7', '9']. ['8', '41', 'Aleix Espargaro', 'Aprilia', '25', '+40.546', '9', '8']. ['9', '14', 'Ratthapark Wilairot', 'Honda', '25', '+1:00.219', '12', '7']. ['10', '32', 'Fabrizio Lai', 'Gilera', '25', '+1:20.825', '13', '6']. ['11', '17', 'Karel Abraham', 'Aprilia', '25', '+1:22.802', '17', '5']. ['12', '25', 'Alex Baldolini', 'Aprilia', '25', '+1:22.864', '18', '4']. ['13', '10', 'Imre Toth', 'Aprilia', '25', '+1:23.995', '16', '3']. ['14', '52', 'Lukas Pesek', 'Aprilia', '25', '+1:39.740', '14', '2']. ['15', '35', 'Simone Grotzkyj', 'Gilera', '24', '+1 Lap', '21', '1']. ['16', '92', 'Daniel Arcas', 'Honda', '24', '+1 Lap', '20', '']. ['17', '45', 'Doni Tata Pradita', 'Yamaha', '24', '+1 Lap', '22', '']. ['Ret', '4', 'Hiroshi Aoyama', 'KTM', '15', 'Retirement', '4', '']. ['Ret', '75', 'Mattia Pasini', 'Aprilia', '15', 'Accident', '10', '']. ['Ret', '55', 'Hector Faubel', 'Aprilia', '4', 'Accident', '5', '']. ['Ret', '90', 'Federico Sandi', 'Aprilia', '1', 'Accident', '15', '']. ['Ret', '43', 'Manuel Hernandez', 'Aprilia', '1', 'Retirement', '19', '']. ['DNQ', '27', 'Stefano Bianco', 'Gilera', '', '', '', '']. ['DNQ', '89', 'Ho Wan Chow', 'Aprilia', '', '', '', '']
Example Output:
how many laps did marco perform?