sail/symbolic-instruction-tuning huggingface dataset:
[Table] header: Rank | Celebrity | Professional Partner | Season | Average row 1 : 1 | Natasza Urbańska | Ján Kliment | 10 | 39.18
row 2 : 2 | Katarzyna Glinka | Stefano Terrazzino | 11 | 38.76
row 3 : 3 | Justyna Steczkowska | Stefano Terrazzino | 6 | 37.67
row 4 : 4 | Paweł Staliński | Izabela Janachowska | 12 | 37.29
row 5 : 5 | Natalia Lesz | Łukasz Czarnecki | 8 | 37.24
row 6 : 6 | Bilguun Ariunbaatar | Janja Lesar | 13 | 36.65
row 7 : 7 | Bartek Kasprzykowski | Blanka Winiarska | 9 | 36.6
row 8 : 8 | Małgorzata Forem | Rafał Maserak | 2 | 36.36
row 9 : 9 | Aleksandra Kwaśniew | Rafał Maserak | 3 | 35.21
row 10 : 10 | Peter J. Lucas | Dominika Kublik-Marzec | 4 | 34.93
row 11 : 11 | Witold Paszt | Anna Głogowska | 1 | 34.66
row 12 : 12 | Ivan Komarenko | Blanka Winiarska | 5 | 33.36
row 13 : 13 | Mariusz Pudzianowski | Magdalena Soszyńska- | 7 | 33.06 [/Table] Answer this question based on the above table: Who is the professional partner of celebrity małgorzata foremniak with a season less than 7, an average greater than 34.66, and a rank less than 10?

Answer: none
[Table] header: Administrative Panel | Agricultural Panel | Cultural and Educational Panel | Industrial and Commercial Panel | Labour Panel | National University of Ireland | University of Dublin | Nominated by the Taoiseach | Total row 1 : 2 | 6 | 1 | 3 | 0 | 1 | 0 | 8 | 21
row 2 : 2 | 1 | 2 | 2 | 1 | 2 | 0 | 0 | 10
row 3 : 0 | 0 | 1 | 0 | 5 | 0 | 0 | 1 | 7
row 4 : 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1
row 5 : 1 | 1 | 0 | 0 | 1 | 0 | 3 | 2 | 8
row 6 : 7 | 11 | 5 | 9 | 11 | 3 | 3 | 11 | 60 [/Table] Answer this question based on the above table: What is the average agricultural panel value with a Labour panel less than 1, a total value less than 21, and a National University of Ireland value greater than 0?

Answer: none
[Table] header: Administrative Panel | Agricultural Panel | Cultural and Educational Panel | Industrial and Commercial Panel | Labour Panel | National University of Ireland | University of Dublin | Nominated by the Taoiseach | Total row 1 : 2 | 6 | 1 | 3 | 0 | 1 | 0 | 8 | 21
row 2 : 2 | 1 | 2 | 2 | 1 | 2 | 0 | 0 | 10
row 3 : 0 | 0 | 1 | 0 | 5 | 0 | 0 | 1 | 7
row 4 : 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1
row 5 : 1 | 1 | 0 | 0 | 1 | 0 | 3 | 2 | 8
row 6 : 7 | 11 | 5 | 9 | 11 | 3 | 3 | 11 | 60 [/Table] Answer this question based on the above table: What is the highest administrative panel value with an agricultural panel less than 1 and a labour panel value less than 5?

Answer: none
[Table] header: Administrative Panel | Agricultural Panel | Cultural and Educational Panel | Industrial and Commercial Panel | Labour Panel | National University of Ireland | University of Dublin | Nominated by the Taoiseach | Total row 1 : 2 | 6 | 1 | 3 | 0 | 1 | 0 | 8 | 21
row 2 : 2 | 1 | 2 | 2 | 1 | 2 | 0 | 0 | 10
row 3 : 0 | 0 | 1 | 0 | 5 | 0 | 0 | 1 | 7
row 4 : 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1
row 5 : 1 | 1 | 0 | 0 | 1 | 0 | 3 | 2 | 8
row 6 : 7 | 11 | 5 | 9 | 11 | 3 | 3 | 11 | 60 [/Table] Answer this question based on the above table: What is the highest labour panel value with a cultural and educational panel greater than 1, a University of Dublin value greater than 0, and a total value less than 60?

Answer: none
[Table] header: Administrative Panel | Agricultural Panel | Cultural and Educational Panel | Industrial and Commercial Panel | Labour Panel | National University of Ireland | University of Dublin | Nominated by the Taoiseach | Total row 1 : 2 | 6 | 1 | 3 | 0 | 1 | 0 | 8 | 21
row 2 : 2 | 1 | 2 | 2 | 1 | 2 | 0 | 0 | 10
row 3 : 0 | 0 | 1 | 0 | 5 | 0 | 0 | 1 | 7
row 4 : 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1
row 5 : 1 | 1 | 0 | 0 | 1 | 0 | 3 | 2 | 8
row 6 : 7 | 11 | 5 | 9 | 11 | 3 | 3 | 11 | 60 [/Table] Answer this question based on the above table: What is the total University of Dublin value with a labour panel greater than 11?

Answer: 0.0
[Table] header: Administrative Panel | Agricultural Panel | Cultural and Educational Panel | Industrial and Commercial Panel | Labour Panel | National University of Ireland | University of Dublin | Nominated by the Taoiseach | Total row 1 : 2 | 6 | 1 | 3 | 0 | 1 | 0 | 8 | 21
row 2 : 2 | 1 | 2 | 2 | 1 | 2 | 0 | 0 | 10
row 3 : 0 | 0 | 1 | 0 | 5 | 0 | 0 | 1 | 7
row 4 : 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1
row 5 : 1 | 1 | 0 | 0 | 1 | 0 | 3 | 2 | 8
row 6 : 7 | 11 | 5 | 9 | 11 | 3 | 3 | 11 | 60 [/Table] Answer this question based on the above table: What is the sum of the cultural and educational panel value with an administrative panel of 0 and an agricultural panel value less than 0?

Answer: none
[Table] header: Country | 2010 | 2011 | 2012 | 2013 row 1 : Romania | 887,763 | 968,576 | 997,000 | n.a.
row 2 : Morocco | 431,529 | 452,424 | 506,369 | 513,374
row 3 : Albania | 466,684 | 482,627 | 491,495 | 497,761
row 4 : China | 188,352 | 209,934 | 277,570 | 304,768
row 5 : Ukraine | 174,129 | 200,730 | 223,782 | 224,588
row 6 : Philippines | 123,584 | 134,154 | 152,382 | 158,308
row 7 : India | 105,863 | 121,036 | 145,164 | 150,462
row 8 : Moldova | 37.971 | 130,948 | 147,519 | 149,231
row 9 : Egypt | 82,064 | 90,365 | 117,145 | 123,529
row 10 : Tunisia | 103,678 | 106,291 | 122,595 | 121,483
row 11 : Bangladesh | 73,965 | 82,451 | 106,671 | 113,811
row 12 : Poland | 105,608 | 109,018 | 112,000 | n.a.
row 13 : Peru | 87,747 | 98,603 | 107,847 | n.a.
row 14 : Serbia | 53,875 | 52,954 | 101,554 | n.a.
row 15 : Sri Lanka | 75,343 | 81,094 | 94,577 | n.a.
row 16 : Pakistan | 64,859 | 75,720 | 90,185 | n.a.
row 17 : Ecuador | 85,940 | 91,625 | 89,626 | n.a.
row 18 : Senegal | 72,618 | 80,989 | 87,311 | n.a.
row 19 : Macedonia | 92,847 | 89,900 | 82,209 | n.a. [/Table] Answer this question based on the above table: What is the highest 2012 immigration for a country with an immigration of 81,094 in 2011?

Answer: 94577.0
[Table] header: Member State | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 row 1 : Austria | 2.4 | 3.7 | 3.7 | 1.4 | −3.8 | 2.1 | 2.7 | 0.8
row 2 : Belgium | 1.8 | 2.7 | 2.9 | 1.0 | −2.8 | 2.4 | 1.8 | −0.3
row 3 : Bulgaria | 6.4 | 6.5 | 6.4 | 6.2 | −5.5 | 0.4 | 1.8 | 0.8
row 4 : Croatia | 4.2 | 4.9 | 5.1 | 2.1 | −6.9 | -2.3 | 0.0 | -2.0
row 5 : Cyprus | 3.9 | 4.1 | 5.1 | 3.6 | −1.9 | 1.3 | 0.5 | −2.4
row 6 : Czech Republic | 6.8 | 7.0 | 5.7 | 3.1 | −4.5 | 2.5 | 1.9 | −1.3
row 7 : Denmark | 2.4 | 3.4 | 1.6 | −0.8 | −5.7 | 1.6 | 1.1 | −0.5
row 8 : Estonia | 8.9 | 10.1 | 7.5 | −4.2 | −14.1 | 3.3 | 8.3 | 3.2
row 9 : Finland | 2.9 | 4.4 | 5.3 | 0.3 | −8.5 | 3.3 | 2.8 | −0.2
row 10 : France | 1.9 | 2.7 | 2.3 | −0.1 | −3.1 | 1.7 | 2.0 | 0.0
row 11 : Germany | 0.7 | 3.7 | 3.3 | 1.1 | −5.1 | 4.2 | 3.0 | 0.7
row 12 : Greece | 2.3 | 5.5 | 3.5 | −0.2 | −3.1 | −4.9 | −7.1 | −6.4
row 13 : Hungary | 4.0 | 3.9 | 0.1 | 0.9 | −6.8 | 1.3 | 1.6 | −1.7
row 14 : Ireland | 5.9 | 5.4 | 5.4 | −2.1 | −5.5 | −0.8 | 1.4 | 0.9
row 15 : Italy | 0.9 | 2.2 | 1.7 | −1.2 | −5.5 | 1.8 | 0.4 | −2.4
row 16 : Latvia | 10.1 | 11.2 | 9.6 | −3.3 | −17.7 | −0.9 | 5.5 | 5.6
row 17 : Lithuania | 7.8 | 7.8 | 9.8 | 2.9 | −14.8 | 1.5 | 5.9 | 3.7
row 18 : Luxembourg | 5.3 | 4.9 | 6.6 | −0.7 | −4.1 | 2.9 | 1.7 | 0.3
row 19 : Malta | 3.6 | 2.6 | 4.1 | 3.9 | −2.6 | 2.9 | 1.7 | 0.8
row 20 : Netherlands | 2.0 | 3.4 | 3.9 | 1.8 | −3.7 | 1.6 | 1.0 | −1.0
row 21 : Poland | 3.6 | 6.2 | 6.8 | 5.1 | 1.6 | 3.9 | 4.5 | 1.9
row 22 : Portugal | 0.8 | 1.4 | 2.4 | 0.0 | −2.9 | 1.9 | −1.6 | −3.2
row 23 : Romania | 4.2 | 7.9 | 6.3 | 7.3 | −6.6 | −1.1 | 2.2 | 0.7
row 24 : Spain | 3.6 | 4.1 | 3.5 | 0.9 | −3.7 | −0.3 | 0.4 | −1.4
row 25 : Slovakia | 6.7 | 8.3 | 10.5 | 5.8 | −4.9 | 4.4 | 3.2 | 2.0
row 26 : Slovenia | 4.0 | 5.8 | 7.0 | 3.4 | −7.8 | 1.2 | 0.6 | −2.3
row 27 : Sweden | 3.2 | 4.3 | 3.3 | −0.6 | −5.0 | 6.6 | 3.7 | 0.7
row 28 : United Kingdom | 2.8 | 2.6 | 3.6 | −1.0 | −4.0 | 1.8 | 1.0 | 0.3
row 29 : European Union | 2.1 | 3.3 | 3.2 | 0.3 | −4.3 | 2.1 | 1.6 | −0.3
row 30 : Eurozone | 1.7 | 3.2 | 3.0 | 0.4 | −4.4 | 2.0 | 1.4 | −0.6 [/Table] Answer this question based on the above table: What is the 2011 value with a 2008 value of 0.3 and is a member state of the European Union?

Answer: 1.6
[Table] header: Member State | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 row 1 : Austria | 2.4 | 3.7 | 3.7 | 1.4 | −3.8 | 2.1 | 2.7 | 0.8
row 2 : Belgium | 1.8 | 2.7 | 2.9 | 1.0 | −2.8 | 2.4 | 1.8 | −0.3
row 3 : Bulgaria | 6.4 | 6.5 | 6.4 | 6.2 | −5.5 | 0.4 | 1.8 | 0.8
row 4 : Croatia | 4.2 | 4.9 | 5.1 | 2.1 | −6.9 | -2.3 | 0.0 | -2.0
row 5 : Cyprus | 3.9 | 4.1 | 5.1 | 3.6 | −1.9 | 1.3 | 0.5 | −2.4
row 6 : Czech Republic | 6.8 | 7.0 | 5.7 | 3.1 | −4.5 | 2.5 | 1.9 | −1.3
row 7 : Denmark | 2.4 | 3.4 | 1.6 | −0.8 | −5.7 | 1.6 | 1.1 | −0.5
row 8 : Estonia | 8.9 | 10.1 | 7.5 | −4.2 | −14.1 | 3.3 | 8.3 | 3.2
row 9 : Finland | 2.9 | 4.4 | 5.3 | 0.3 | −8.5 | 3.3 | 2.8 | −0.2
row 10 : France | 1.9 | 2.7 | 2.3 | −0.1 | −3.1 | 1.7 | 2.0 | 0.0
row 11 : Germany | 0.7 | 3.7 | 3.3 | 1.1 | −5.1 | 4.2 | 3.0 | 0.7
row 12 : Greece | 2.3 | 5.5 | 3.5 | −0.2 | −3.1 | −4.9 | −7.1 | −6.4
row 13 : Hungary | 4.0 | 3.9 | 0.1 | 0.9 | −6.8 | 1.3 | 1.6 | −1.7
row 14 : Ireland | 5.9 | 5.4 | 5.4 | −2.1 | −5.5 | −0.8 | 1.4 | 0.9
row 15 : Italy | 0.9 | 2.2 | 1.7 | −1.2 | −5.5 | 1.8 | 0.4 | −2.4
row 16 : Latvia | 10.1 | 11.2 | 9.6 | −3.3 | −17.7 | −0.9 | 5.5 | 5.6
row 17 : Lithuania | 7.8 | 7.8 | 9.8 | 2.9 | −14.8 | 1.5 | 5.9 | 3.7
row 18 : Luxembourg | 5.3 | 4.9 | 6.6 | −0.7 | −4.1 | 2.9 | 1.7 | 0.3
row 19 : Malta | 3.6 | 2.6 | 4.1 | 3.9 | −2.6 | 2.9 | 1.7 | 0.8
row 20 : Netherlands | 2.0 | 3.4 | 3.9 | 1.8 | −3.7 | 1.6 | 1.0 | −1.0
row 21 : Poland | 3.6 | 6.2 | 6.8 | 5.1 | 1.6 | 3.9 | 4.5 | 1.9
row 22 : Portugal | 0.8 | 1.4 | 2.4 | 0.0 | −2.9 | 1.9 | −1.6 | −3.2
row 23 : Romania | 4.2 | 7.9 | 6.3 | 7.3 | −6.6 | −1.1 | 2.2 | 0.7
row 24 : Spain | 3.6 | 4.1 | 3.5 | 0.9 | −3.7 | −0.3 | 0.4 | −1.4
row 25 : Slovakia | 6.7 | 8.3 | 10.5 | 5.8 | −4.9 | 4.4 | 3.2 | 2.0
row 26 : Slovenia | 4.0 | 5.8 | 7.0 | 3.4 | −7.8 | 1.2 | 0.6 | −2.3
row 27 : Sweden | 3.2 | 4.3 | 3.3 | −0.6 | −5.0 | 6.6 | 3.7 | 0.7
row 28 : United Kingdom | 2.8 | 2.6 | 3.6 | −1.0 | −4.0 | 1.8 | 1.0 | 0.3
row 29 : European Union | 2.1 | 3.3 | 3.2 | 0.3 | −4.3 | 2.1 | 1.6 | −0.3
row 30 : Eurozone | 1.7 | 3.2 | 3.0 | 0.4 | −4.4 | 2.0 | 1.4 | −0.6 [/Table] Answer this question based on the above table: What is the 2012 value with a 1.3 in 2010 and a 3.6 in 2008?

Answer: −2.4
[Table] header: Category | Frequency | White | Brown | Black | Amerindian | Yellow | Total row 1 : vermelha (Red) | 0.02% | 58,97 | 8,22 | 0,00 | 21,56 | 11,24 | 100,00
row 2 : cafusa | 0.01% | 6,02 | 65,14 | 22,82 | 6,02 | 0,00 | 100,00
row 3 : caboverde (Capeverdian) | 0.02% | 0,00 | 48,72 | 23,08 | 28,21 | 0,00 | 100,00
row 4 : cabocla | 0.02% | 3,60 | 49,37 | 10,43 | 36,60 | 0,00 | 100,00
row 5 : bugre (Indian) | 0.00% | 12,50 | 37,50 | 0,00 | 50,00 | 0,00 | 100,00
row 6 : amarela (Yellow) | 1.11% | 3,27 | 0,98 | 0,24 | 0,15 | 95,36 | 100,00
row 7 : indígena (Indigenous | 0.13% | 0,44 | 2,12 | 0,00 | 96,13 | 1,30 | 100,00 [/Table] Answer this question based on the above table: What is the average Black, when White is less than 6,02, and when Total is greater than 100,00?

Answer: none
[Table] header: Category | Frequency | White | Brown | Black | Amerindian | Yellow | Total row 1 : vermelha (Red) | 0.02% | 58,97 | 8,22 | 0,00 | 21,56 | 11,24 | 100,00
row 2 : cafusa | 0.01% | 6,02 | 65,14 | 22,82 | 6,02 | 0,00 | 100,00
row 3 : caboverde (Capeverdian) | 0.02% | 0,00 | 48,72 | 23,08 | 28,21 | 0,00 | 100,00
row 4 : cabocla | 0.02% | 3,60 | 49,37 | 10,43 | 36,60 | 0,00 | 100,00
row 5 : bugre (Indian) | 0.00% | 12,50 | 37,50 | 0,00 | 50,00 | 0,00 | 100,00
row 6 : amarela (Yellow) | 1.11% | 3,27 | 0,98 | 0,24 | 0,15 | 95,36 | 100,00
row 7 : indígena (Indigenous | 0.13% | 0,44 | 2,12 | 0,00 | 96,13 | 1,30 | 100,00 [/Table] Answer this question based on the above table: What is the sum of Yellow, when Category is Bugre (Indian), and when Amerindian is less than 50,00?

Answer: none
[Table] header: Category | Frequency | White | Brown | Black | Amerindian | Yellow | Total row 1 : vermelha (Red) | 0.02% | 58,97 | 8,22 | 0,00 | 21,56 | 11,24 | 100,00
row 2 : cafusa | 0.01% | 6,02 | 65,14 | 22,82 | 6,02 | 0,00 | 100,00
row 3 : caboverde (Capeverdian) | 0.02% | 0,00 | 48,72 | 23,08 | 28,21 | 0,00 | 100,00
row 4 : cabocla | 0.02% | 3,60 | 49,37 | 10,43 | 36,60 | 0,00 | 100,00
row 5 : bugre (Indian) | 0.00% | 12,50 | 37,50 | 0,00 | 50,00 | 0,00 | 100,00
row 6 : amarela (Yellow) | 1.11% | 3,27 | 0,98 | 0,24 | 0,15 | 95,36 | 100,00
row 7 : indígena (Indigenous | 0.13% | 0,44 | 2,12 | 0,00 | 96,13 | 1,30 | 100,00 [/Table] Answer this question based on the above table: What is the sum of Amerindian, when White is 6,02, and when Total is greater than 100,00?

Answer: none
[Table] header: Order | Artist | Song | Lyrics (l) / Music (m) | Results row 1 : 1 | Zuma | "Always, Always" | Alexander Stenerud (m &  | Siste Sjansen
row 2 : 2 | Cube | "Would You Spend the Night With Me | Åge Sten "Glam" | Out
row 3 : 3 | Anne Hvidsten | "A Little More" | Anne Hvidsten (m & l | Siste Sjansen
row 4 : 4 | Crash! | "Get Up" | Trond "Teeny" Holter | Final
row 5 : 5 | Sven Garås | "I'm in Love" | Robin Nordahl (m), Ingri | Out
row 6 : 6 | Maria Haukaas Storeng | "Hold On Be Strong" | Mira Craig (m & l) | Final [/Table] Answer this question based on the above table: Who provided lyrics or music to the artist Cube?

Answer: Åge Sten "Glam"
[Table] header: Location | Aircraft | Tail number | Aircraft damage | Fatalities row 1 : Mogadishu | Viscount 700 | 6O-AAJ | W/O | 5/30
row 2 : Bosaso | Douglas C-47A | 6O-SAC | W/O | 0/11
row 3 : Balad | F-27-600RF | 6O-SAY | W/O | 50/50
row 4 : Nairobi | Boeing 707-320B | 6O-SBT | W/O | 0/70
row 5 : Hargeisa | F-27-600RF | 6O-SAZ | W/O | 30/30 [/Table] Answer this question based on the above table: What was the aircraft damage for the Boeing 707-320B?

Answer: W/O
[Table] header: Location | Aircraft | Tail number | Aircraft damage | Fatalities row 1 : Mogadishu | Viscount 700 | 6O-AAJ | W/O | 5/30
row 2 : Bosaso | Douglas C-47A | 6O-SAC | W/O | 0/11
row 3 : Balad | F-27-600RF | 6O-SAY | W/O | 50/50
row 4 : Nairobi | Boeing 707-320B | 6O-SBT | W/O | 0/70
row 5 : Hargeisa | F-27-600RF | 6O-SAZ | W/O | 30/30 [/Table] Answer this question based on the above table: What was the number of fatalities for the Viscount 700?

Answer: 5/30
[Table] header: Location | Aircraft | Tail number | Aircraft damage | Fatalities row 1 : Mogadishu | Viscount 700 | 6O-AAJ | W/O | 5/30
row 2 : Bosaso | Douglas C-47A | 6O-SAC | W/O | 0/11
row 3 : Balad | F-27-600RF | 6O-SAY | W/O | 50/50
row 4 : Nairobi | Boeing 707-320B | 6O-SBT | W/O | 0/70
row 5 : Hargeisa | F-27-600RF | 6O-SAZ | W/O | 30/30 [/Table] Answer this question based on the above table: What was the aircraft damage for the accident that had fatalities of 30/30?

Answer: W/O
[Table] header: Location | Aircraft | Tail number | Aircraft damage | Fatalities row 1 : Mogadishu | Viscount 700 | 6O-AAJ | W/O | 5/30
row 2 : Bosaso | Douglas C-47A | 6O-SAC | W/O | 0/11
row 3 : Balad | F-27-600RF | 6O-SAY | W/O | 50/50
row 4 : Nairobi | Boeing 707-320B | 6O-SBT | W/O | 0/70
row 5 : Hargeisa | F-27-600RF | 6O-SAZ | W/O | 30/30 [/Table] Answer this question based on the above table: What was the location that had an accident by the F-27-600RF aircraft with tail number 6O-SAZ?

Answer: Hargeisa
[Table] header: Location | Aircraft | Tail number | Aircraft damage | Fatalities row 1 : Mogadishu | Viscount 700 | 6O-AAJ | W/O | 5/30
row 2 : Bosaso | Douglas C-47A | 6O-SAC | W/O | 0/11
row 3 : Balad | F-27-600RF | 6O-SAY | W/O | 50/50
row 4 : Nairobi | Boeing 707-320B | 6O-SBT | W/O | 0/70
row 5 : Hargeisa | F-27-600RF | 6O-SAZ | W/O | 30/30 [/Table] Answer this question based on the above table: What was the tail number of the aircraft that had 5/30 fatalities?

Answer: 6O-AAJ
[Table] header: Location | Aircraft | Tail number | Aircraft damage | Fatalities row 1 : Mogadishu | Viscount 700 | 6O-AAJ | W/O | 5/30
row 2 : Bosaso | Douglas C-47A | 6O-SAC | W/O | 0/11
row 3 : Balad | F-27-600RF | 6O-SAY | W/O | 50/50
row 4 : Nairobi | Boeing 707-320B | 6O-SBT | W/O | 0/70
row 5 : Hargeisa | F-27-600RF | 6O-SAZ | W/O | 30/30 [/Table] Answer this question based on the above table: What was the location of the accident that led to 50/50 fatalities?

Answer: Balad
[Table] header: Year | Team | SckY | Int% | Rate | RAtt | RYds | RAvg | RLng | R1st row 1 : 1991 | ATL | 11 | 50.0 | 0.0 | 0 | 0 | 0.0 | 0 | 0
row 2 : 1992 | GB | 208 | 2.8 | 85.3 | 47 | 198 | 4.2 | 19 | 11
row 3 : 1993 | GB | 199 | 4.6 | 72.2 | 58 | 216 | 3.7 | 27 | 13
row 4 : 1994 | GB | 188 | 2.4 | 90.7 | 42 | 202 | 4.8 | 36 | 14
row 5 : 1995 | GB | 217 | 2.3 | 99.5 | 39 | 181 | 4.6 | 40 | 17
row 6 : 1996 | GB | 241 | 2.4 | 95.8 | 49 | 136 | 2.8 | 23 | 18
row 7 : 1997 | GB | 176 | 3.1 | 92.6 | 58 | 187 | 3.2 | 16 | 16
row 8 : 1998 | GB | 223 | 4.2 | 87.8 | 40 | 133 | 3.3 | 35 | 13
row 9 : 1999 | GB | 223 | 3.9 | 74.7 | 28 | 142 | 5.1 | 20 | 11
row 10 : 2000 | GB | 236 | 2.8 | 78.0 | 27 | 108 | 4.0 | 18 | 7
row 11 : 2001 | GB | 151 | 2.9 | 94.1 | 38 | 56 | 1.5 | 14 | 5
row 12 : 2002 | GB | 188 | 2.9 | 85.6 | 25 | 73 | 2.9 | 17 | 6
row 13 : 2003 | GB | 137 | 4.5 | 90.4 | 18 | 15 | 0.8 | 7 | 3
row 14 : 2004 | GB | 93 | 3.1 | 92.4 | 16 | 36 | 2.3 | 17 | 2
row 15 : 2005 | GB | 170 | 4.8 | 70.9 | 18 | 62 | 3.4 | 20 | 4
row 16 : 2006 | GB | 134 | 2.9 | 72.7 | 23 | 29 | 1.3 | 14 | 4
row 17 : 2007 | GB | 93 | 2.8 | 95.7 | 29 | 12 | 0.4 | 21 | 3
row 18 : 2008 | NYJ | 213 | 4.2 | 81.0 | 21 | 43 | 2.0 | 27 | 4
row 19 : 2009 | MIN | 247 | 1.4 | 107.2 | 9 | 7 | 0.8 | 4 | 1
row 20 : 2010 | MIN | 139 | 5.3 | 69.9 | 17 | 8 | 0.5 | 10 | 1
row 21 : Career | Career | SckY | Int% | Rate | RAtt | RYds | RAvg | RLng | R1st
row 22 : 20Years | 20Years | 3,487 | 3.3 | 86.0 | 602 | 1,844 | 3.1 | 40 | 153 [/Table] Answer this question based on the above table: What % has 4 RLng?

Answer: 1.4
[Table] header: Year | Team | SckY | Int% | Rate | RAtt | RYds | RAvg | RLng | R1st row 1 : 1991 | ATL | 11 | 50.0 | 0.0 | 0 | 0 | 0.0 | 0 | 0
row 2 : 1992 | GB | 208 | 2.8 | 85.3 | 47 | 198 | 4.2 | 19 | 11
row 3 : 1993 | GB | 199 | 4.6 | 72.2 | 58 | 216 | 3.7 | 27 | 13
row 4 : 1994 | GB | 188 | 2.4 | 90.7 | 42 | 202 | 4.8 | 36 | 14
row 5 : 1995 | GB | 217 | 2.3 | 99.5 | 39 | 181 | 4.6 | 40 | 17
row 6 : 1996 | GB | 241 | 2.4 | 95.8 | 49 | 136 | 2.8 | 23 | 18
row 7 : 1997 | GB | 176 | 3.1 | 92.6 | 58 | 187 | 3.2 | 16 | 16
row 8 : 1998 | GB | 223 | 4.2 | 87.8 | 40 | 133 | 3.3 | 35 | 13
row 9 : 1999 | GB | 223 | 3.9 | 74.7 | 28 | 142 | 5.1 | 20 | 11
row 10 : 2000 | GB | 236 | 2.8 | 78.0 | 27 | 108 | 4.0 | 18 | 7
row 11 : 2001 | GB | 151 | 2.9 | 94.1 | 38 | 56 | 1.5 | 14 | 5
row 12 : 2002 | GB | 188 | 2.9 | 85.6 | 25 | 73 | 2.9 | 17 | 6
row 13 : 2003 | GB | 137 | 4.5 | 90.4 | 18 | 15 | 0.8 | 7 | 3
row 14 : 2004 | GB | 93 | 3.1 | 92.4 | 16 | 36 | 2.3 | 17 | 2
row 15 : 2005 | GB | 170 | 4.8 | 70.9 | 18 | 62 | 3.4 | 20 | 4
row 16 : 2006 | GB | 134 | 2.9 | 72.7 | 23 | 29 | 1.3 | 14 | 4
row 17 : 2007 | GB | 93 | 2.8 | 95.7 | 29 | 12 | 0.4 | 21 | 3
row 18 : 2008 | NYJ | 213 | 4.2 | 81.0 | 21 | 43 | 2.0 | 27 | 4
row 19 : 2009 | MIN | 247 | 1.4 | 107.2 | 9 | 7 | 0.8 | 4 | 1
row 20 : 2010 | MIN | 139 | 5.3 | 69.9 | 17 | 8 | 0.5 | 10 | 1
row 21 : Career | Career | SckY | Int% | Rate | RAtt | RYds | RAvg | RLng | R1st
row 22 : 20Years | 20Years | 3,487 | 3.3 | 86.0 | 602 | 1,844 | 3.1 | 40 | 153 [/Table] Answer this question based on the above table: What team had a Ravg of 3.4?

Answer: GB
[Table] header: Year | Team | SckY | Int% | Rate | RAtt | RYds | RAvg | RLng | R1st row 1 : 1991 | ATL | 11 | 50.0 | 0.0 | 0 | 0 | 0.0 | 0 | 0
row 2 : 1992 | GB | 208 | 2.8 | 85.3 | 47 | 198 | 4.2 | 19 | 11
row 3 : 1993 | GB | 199 | 4.6 | 72.2 | 58 | 216 | 3.7 | 27 | 13
row 4 : 1994 | GB | 188 | 2.4 | 90.7 | 42 | 202 | 4.8 | 36 | 14
row 5 : 1995 | GB | 217 | 2.3 | 99.5 | 39 | 181 | 4.6 | 40 | 17
row 6 : 1996 | GB | 241 | 2.4 | 95.8 | 49 | 136 | 2.8 | 23 | 18
row 7 : 1997 | GB | 176 | 3.1 | 92.6 | 58 | 187 | 3.2 | 16 | 16
row 8 : 1998 | GB | 223 | 4.2 | 87.8 | 40 | 133 | 3.3 | 35 | 13
row 9 : 1999 | GB | 223 | 3.9 | 74.7 | 28 | 142 | 5.1 | 20 | 11
row 10 : 2000 | GB | 236 | 2.8 | 78.0 | 27 | 108 | 4.0 | 18 | 7
row 11 : 2001 | GB | 151 | 2.9 | 94.1 | 38 | 56 | 1.5 | 14 | 5
row 12 : 2002 | GB | 188 | 2.9 | 85.6 | 25 | 73 | 2.9 | 17 | 6
row 13 : 2003 | GB | 137 | 4.5 | 90.4 | 18 | 15 | 0.8 | 7 | 3
row 14 : 2004 | GB | 93 | 3.1 | 92.4 | 16 | 36 | 2.3 | 17 | 2
row 15 : 2005 | GB | 170 | 4.8 | 70.9 | 18 | 62 | 3.4 | 20 | 4
row 16 : 2006 | GB | 134 | 2.9 | 72.7 | 23 | 29 | 1.3 | 14 | 4
row 17 : 2007 | GB | 93 | 2.8 | 95.7 | 29 | 12 | 0.4 | 21 | 3
row 18 : 2008 | NYJ | 213 | 4.2 | 81.0 | 21 | 43 | 2.0 | 27 | 4
row 19 : 2009 | MIN | 247 | 1.4 | 107.2 | 9 | 7 | 0.8 | 4 | 1
row 20 : 2010 | MIN | 139 | 5.3 | 69.9 | 17 | 8 | 0.5 | 10 | 1
row 21 : Career | Career | SckY | Int% | Rate | RAtt | RYds | RAvg | RLng | R1st
row 22 : 20Years | 20Years | 3,487 | 3.3 | 86.0 | 602 | 1,844 | 3.1 | 40 | 153 [/Table] Answer this question based on the above table: What is the int percentage that has Ravg of 2.8?

Answer: 2.4
[Table] header: Year | Team | SckY | Int% | Rate | RAtt | RYds | RAvg | RLng | R1st row 1 : 1991 | ATL | 11 | 50.0 | 0.0 | 0 | 0 | 0.0 | 0 | 0
row 2 : 1992 | GB | 208 | 2.8 | 85.3 | 47 | 198 | 4.2 | 19 | 11
row 3 : 1993 | GB | 199 | 4.6 | 72.2 | 58 | 216 | 3.7 | 27 | 13
row 4 : 1994 | GB | 188 | 2.4 | 90.7 | 42 | 202 | 4.8 | 36 | 14
row 5 : 1995 | GB | 217 | 2.3 | 99.5 | 39 | 181 | 4.6 | 40 | 17
row 6 : 1996 | GB | 241 | 2.4 | 95.8 | 49 | 136 | 2.8 | 23 | 18
row 7 : 1997 | GB | 176 | 3.1 | 92.6 | 58 | 187 | 3.2 | 16 | 16
row 8 : 1998 | GB | 223 | 4.2 | 87.8 | 40 | 133 | 3.3 | 35 | 13
row 9 : 1999 | GB | 223 | 3.9 | 74.7 | 28 | 142 | 5.1 | 20 | 11
row 10 : 2000 | GB | 236 | 2.8 | 78.0 | 27 | 108 | 4.0 | 18 | 7
row 11 : 2001 | GB | 151 | 2.9 | 94.1 | 38 | 56 | 1.5 | 14 | 5
row 12 : 2002 | GB | 188 | 2.9 | 85.6 | 25 | 73 | 2.9 | 17 | 6
row 13 : 2003 | GB | 137 | 4.5 | 90.4 | 18 | 15 | 0.8 | 7 | 3
row 14 : 2004 | GB | 93 | 3.1 | 92.4 | 16 | 36 | 2.3 | 17 | 2
row 15 : 2005 | GB | 170 | 4.8 | 70.9 | 18 | 62 | 3.4 | 20 | 4
row 16 : 2006 | GB | 134 | 2.9 | 72.7 | 23 | 29 | 1.3 | 14 | 4
row 17 : 2007 | GB | 93 | 2.8 | 95.7 | 29 | 12 | 0.4 | 21 | 3
row 18 : 2008 | NYJ | 213 | 4.2 | 81.0 | 21 | 43 | 2.0 | 27 | 4
row 19 : 2009 | MIN | 247 | 1.4 | 107.2 | 9 | 7 | 0.8 | 4 | 1
row 20 : 2010 | MIN | 139 | 5.3 | 69.9 | 17 | 8 | 0.5 | 10 | 1
row 21 : Career | Career | SckY | Int% | Rate | RAtt | RYds | RAvg | RLng | R1st
row 22 : 20Years | 20Years | 3,487 | 3.3 | 86.0 | 602 | 1,844 | 3.1 | 40 | 153 [/Table] Answer this question based on the above table: Who is the R1st that has 36 RYds?

Answer: 2.0
[Table] header: Year | Team | SckY | Int% | Rate | RAtt | RYds | RAvg | RLng | R1st row 1 : 1991 | ATL | 11 | 50.0 | 0.0 | 0 | 0 | 0.0 | 0 | 0
row 2 : 1992 | GB | 208 | 2.8 | 85.3 | 47 | 198 | 4.2 | 19 | 11
row 3 : 1993 | GB | 199 | 4.6 | 72.2 | 58 | 216 | 3.7 | 27 | 13
row 4 : 1994 | GB | 188 | 2.4 | 90.7 | 42 | 202 | 4.8 | 36 | 14
row 5 : 1995 | GB | 217 | 2.3 | 99.5 | 39 | 181 | 4.6 | 40 | 17
row 6 : 1996 | GB | 241 | 2.4 | 95.8 | 49 | 136 | 2.8 | 23 | 18
row 7 : 1997 | GB | 176 | 3.1 | 92.6 | 58 | 187 | 3.2 | 16 | 16
row 8 : 1998 | GB | 223 | 4.2 | 87.8 | 40 | 133 | 3.3 | 35 | 13
row 9 : 1999 | GB | 223 | 3.9 | 74.7 | 28 | 142 | 5.1 | 20 | 11
row 10 : 2000 | GB | 236 | 2.8 | 78.0 | 27 | 108 | 4.0 | 18 | 7
row 11 : 2001 | GB | 151 | 2.9 | 94.1 | 38 | 56 | 1.5 | 14 | 5
row 12 : 2002 | GB | 188 | 2.9 | 85.6 | 25 | 73 | 2.9 | 17 | 6
row 13 : 2003 | GB | 137 | 4.5 | 90.4 | 18 | 15 | 0.8 | 7 | 3
row 14 : 2004 | GB | 93 | 3.1 | 92.4 | 16 | 36 | 2.3 | 17 | 2
row 15 : 2005 | GB | 170 | 4.8 | 70.9 | 18 | 62 | 3.4 | 20 | 4
row 16 : 2006 | GB | 134 | 2.9 | 72.7 | 23 | 29 | 1.3 | 14 | 4
row 17 : 2007 | GB | 93 | 2.8 | 95.7 | 29 | 12 | 0.4 | 21 | 3
row 18 : 2008 | NYJ | 213 | 4.2 | 81.0 | 21 | 43 | 2.0 | 27 | 4
row 19 : 2009 | MIN | 247 | 1.4 | 107.2 | 9 | 7 | 0.8 | 4 | 1
row 20 : 2010 | MIN | 139 | 5.3 | 69.9 | 17 | 8 | 0.5 | 10 | 1
row 21 : Career | Career | SckY | Int% | Rate | RAtt | RYds | RAvg | RLng | R1st
row 22 : 20Years | 20Years | 3,487 | 3.3 | 86.0 | 602 | 1,844 | 3.1 | 40 | 153 [/Table] Answer this question based on the above table: What was the Ravg for 2003?

Answer: 0.8
[Table] header: Year | Team | SckY | Int% | Rate | RAtt | RYds | RAvg | RLng | R1st row 1 : 1991 | ATL | 11 | 50.0 | 0.0 | 0 | 0 | 0.0 | 0 | 0
row 2 : 1992 | GB | 208 | 2.8 | 85.3 | 47 | 198 | 4.2 | 19 | 11
row 3 : 1993 | GB | 199 | 4.6 | 72.2 | 58 | 216 | 3.7 | 27 | 13
row 4 : 1994 | GB | 188 | 2.4 | 90.7 | 42 | 202 | 4.8 | 36 | 14
row 5 : 1995 | GB | 217 | 2.3 | 99.5 | 39 | 181 | 4.6 | 40 | 17
row 6 : 1996 | GB | 241 | 2.4 | 95.8 | 49 | 136 | 2.8 | 23 | 18
row 7 : 1997 | GB | 176 | 3.1 | 92.6 | 58 | 187 | 3.2 | 16 | 16
row 8 : 1998 | GB | 223 | 4.2 | 87.8 | 40 | 133 | 3.3 | 35 | 13
row 9 : 1999 | GB | 223 | 3.9 | 74.7 | 28 | 142 | 5.1 | 20 | 11
row 10 : 2000 | GB | 236 | 2.8 | 78.0 | 27 | 108 | 4.0 | 18 | 7
row 11 : 2001 | GB | 151 | 2.9 | 94.1 | 38 | 56 | 1.5 | 14 | 5
row 12 : 2002 | GB | 188 | 2.9 | 85.6 | 25 | 73 | 2.9 | 17 | 6
row 13 : 2003 | GB | 137 | 4.5 | 90.4 | 18 | 15 | 0.8 | 7 | 3
row 14 : 2004 | GB | 93 | 3.1 | 92.4 | 16 | 36 | 2.3 | 17 | 2
row 15 : 2005 | GB | 170 | 4.8 | 70.9 | 18 | 62 | 3.4 | 20 | 4
row 16 : 2006 | GB | 134 | 2.9 | 72.7 | 23 | 29 | 1.3 | 14 | 4
row 17 : 2007 | GB | 93 | 2.8 | 95.7 | 29 | 12 | 0.4 | 21 | 3
row 18 : 2008 | NYJ | 213 | 4.2 | 81.0 | 21 | 43 | 2.0 | 27 | 4
row 19 : 2009 | MIN | 247 | 1.4 | 107.2 | 9 | 7 | 0.8 | 4 | 1
row 20 : 2010 | MIN | 139 | 5.3 | 69.9 | 17 | 8 | 0.5 | 10 | 1
row 21 : Career | Career | SckY | Int% | Rate | RAtt | RYds | RAvg | RLng | R1st
row 22 : 20Years | 20Years | 3,487 | 3.3 | 86.0 | 602 | 1,844 | 3.1 | 40 | 153 [/Table] Answer this question based on the above table: What was the rate for 73 RYds?

Answer: 85.6
[Table] header: Name | Status | Authors | Unit | Location row 1 : Delectosaurus | Valid | Kurkin | Vyazniki Assemblage | Russia
row 2 : Interpresosaurus | Valid | Kurkin | Vyazniki Assemblage | Russia
row 3 : Lumkuia | Valid | Hopson Kitching | Burgersdorp Formation | South Africa
row 4 : Malasaurus | Valid | Tatarinov | Vyazniki Assemblage | Russia
row 5 : Mitredon | Valid | Shapiro Jenkins | Fleming Fjord Formation | Greenland
row 6 : Prozostrodon | Valid | Bonaparte Barberena | Santa Maria Formation | Brazil
row 7 : Riograndia | Valid | Bonaparte Ferigolo Rib | Caturrita Formation | Brazil [/Table] Answer this question based on the above table: What is the name of the non-mammal from brazil of the unit of caturrita formation?

Answer: Riograndia
[Table] header: Name | Status | Authors | Unit | Location row 1 : Delectosaurus | Valid | Kurkin | Vyazniki Assemblage | Russia
row 2 : Interpresosaurus | Valid | Kurkin | Vyazniki Assemblage | Russia
row 3 : Lumkuia | Valid | Hopson Kitching | Burgersdorp Formation | South Africa
row 4 : Malasaurus | Valid | Tatarinov | Vyazniki Assemblage | Russia
row 5 : Mitredon | Valid | Shapiro Jenkins | Fleming Fjord Formation | Greenland
row 6 : Prozostrodon | Valid | Bonaparte Barberena | Santa Maria Formation | Brazil
row 7 : Riograndia | Valid | Bonaparte Ferigolo Rib | Caturrita Formation | Brazil [/Table] Answer this question based on the above table: What is the name of the non-mammal who has tatarinov as the author?

Answer: Malasaurus
[Table] header: Name | Status | Authors | Unit | Location row 1 : Delectosaurus | Valid | Kurkin | Vyazniki Assemblage | Russia
row 2 : Interpresosaurus | Valid | Kurkin | Vyazniki Assemblage | Russia
row 3 : Lumkuia | Valid | Hopson Kitching | Burgersdorp Formation | South Africa
row 4 : Malasaurus | Valid | Tatarinov | Vyazniki Assemblage | Russia
row 5 : Mitredon | Valid | Shapiro Jenkins | Fleming Fjord Formation | Greenland
row 6 : Prozostrodon | Valid | Bonaparte Barberena | Santa Maria Formation | Brazil
row 7 : Riograndia | Valid | Bonaparte Ferigolo Rib | Caturrita Formation | Brazil [/Table] Answer this question based on the above table: What is the unit of the non-mammal from greenland?

Answer: Fleming Fjord Formation
[Table] header: Name | Status | Authors | Unit | Location row 1 : Delectosaurus | Valid | Kurkin | Vyazniki Assemblage | Russia
row 2 : Interpresosaurus | Valid | Kurkin | Vyazniki Assemblage | Russia
row 3 : Lumkuia | Valid | Hopson Kitching | Burgersdorp Formation | South Africa
row 4 : Malasaurus | Valid | Tatarinov | Vyazniki Assemblage | Russia
row 5 : Mitredon | Valid | Shapiro Jenkins | Fleming Fjord Formation | Greenland
row 6 : Prozostrodon | Valid | Bonaparte Barberena | Santa Maria Formation | Brazil
row 7 : Riograndia | Valid | Bonaparte Ferigolo Rib | Caturrita Formation | Brazil [/Table] Answer this question based on the above table: Who is the author for the malasaurus?

Answer: Tatarinov
[Table] header: Name | Status | Authors | Unit | Location row 1 : Delectosaurus | Valid | Kurkin | Vyazniki Assemblage | Russia
row 2 : Interpresosaurus | Valid | Kurkin | Vyazniki Assemblage | Russia
row 3 : Lumkuia | Valid | Hopson Kitching | Burgersdorp Formation | South Africa
row 4 : Malasaurus | Valid | Tatarinov | Vyazniki Assemblage | Russia
row 5 : Mitredon | Valid | Shapiro Jenkins | Fleming Fjord Formation | Greenland
row 6 : Prozostrodon | Valid | Bonaparte Barberena | Santa Maria Formation | Brazil
row 7 : Riograndia | Valid | Bonaparte Ferigolo Rib | Caturrita Formation | Brazil [/Table] Answer this question based on the above table: What is the name of the non mammal of the unit vyazniki assemblage?

Answer: Delectosaurus, Interpresosaurus, Malasaurus
[Table] header: Name | Status | Authors | Unit | Location row 1 : Delectosaurus | Valid | Kurkin | Vyazniki Assemblage | Russia
row 2 : Interpresosaurus | Valid | Kurkin | Vyazniki Assemblage | Russia
row 3 : Lumkuia | Valid | Hopson Kitching | Burgersdorp Formation | South Africa
row 4 : Malasaurus | Valid | Tatarinov | Vyazniki Assemblage | Russia
row 5 : Mitredon | Valid | Shapiro Jenkins | Fleming Fjord Formation | Greenland
row 6 : Prozostrodon | Valid | Bonaparte Barberena | Santa Maria Formation | Brazil
row 7 : Riograndia | Valid | Bonaparte Ferigolo Rib | Caturrita Formation | Brazil [/Table] Answer this question based on the above table: Who are the authors for the malasaurus of the vyazniki assemblage?

Answer: Tatarinov
[Table] header: Rank | Nation | Gold | Silver | Bronze | Total row 1 : 1 | United States | 26 | 21 | 24 | 71
row 2 : 2 | Norway | 10 | 1 | 2 | 13
row 3 : 3 | East Germany | 9 | 8 | 2 | 19
row 4 : 4 | Austria | 7 | 17 | 12 | 36
row 5 : 5 | Japan | 7 | 3 | 6 | 16
row 6 : 6 | Hungary | 7 | 1 | 3 | 11
row 7 : 7 | Great Britain | 6 | 9 | 7 | 22
row 8 : 8 | Canada | 4 | 5 | 4 | 13
row 9 : 9 | Netherlands | 4 | 1 | 3 | 8
row 10 : 10 | Russia | 3 | 5 | 4 | 12
row 11 : 11 | South Korea | 2 | 2 | 2 | 6
row 12 : 12 | Czechoslovakia | 2 | 0 | 3 | 5
row 13 : 13 | Germany | 1 | 8 | 4 | 13
row 14 : 14 | France | 1 | 4 | 2 | 7
row 15 : 15 | Italy | 1 | 2 | 3 | 6
row 16 : 16 | China | 1 | 1 | 2 | 4
row 17 : 17 | Switzerland | 1 | 0 | 0 | 1
row 18 : 17 | Ukraine | 1 | 0 | 0 | 1
row 19 : 19 | Sweden | 0 | 2 | 5 | 7
row 20 : 20 | Soviet Union | 0 | 2 | 1 | 3
row 21 : 21 | Finland | 0 | 0 | 1 | 1 [/Table] Answer this question based on the above table: What is the lowest Rank with more than 0 bronze, 8 silver, and a total of 19, with less than 9 gold?

Answer: none
[Table] header: Rank | Nation | Gold | Silver | Bronze | Total row 1 : 1 | United States | 26 | 21 | 24 | 71
row 2 : 2 | Norway | 10 | 1 | 2 | 13
row 3 : 3 | East Germany | 9 | 8 | 2 | 19
row 4 : 4 | Austria | 7 | 17 | 12 | 36
row 5 : 5 | Japan | 7 | 3 | 6 | 16
row 6 : 6 | Hungary | 7 | 1 | 3 | 11
row 7 : 7 | Great Britain | 6 | 9 | 7 | 22
row 8 : 8 | Canada | 4 | 5 | 4 | 13
row 9 : 9 | Netherlands | 4 | 1 | 3 | 8
row 10 : 10 | Russia | 3 | 5 | 4 | 12
row 11 : 11 | South Korea | 2 | 2 | 2 | 6
row 12 : 12 | Czechoslovakia | 2 | 0 | 3 | 5
row 13 : 13 | Germany | 1 | 8 | 4 | 13
row 14 : 14 | France | 1 | 4 | 2 | 7
row 15 : 15 | Italy | 1 | 2 | 3 | 6
row 16 : 16 | China | 1 | 1 | 2 | 4
row 17 : 17 | Switzerland | 1 | 0 | 0 | 1
row 18 : 17 | Ukraine | 1 | 0 | 0 | 1
row 19 : 19 | Sweden | 0 | 2 | 5 | 7
row 20 : 20 | Soviet Union | 0 | 2 | 1 | 3
row 21 : 21 | Finland | 0 | 0 | 1 | 1 [/Table] Answer this question based on the above table: What is the sum for gold when there is more than 17 silver and more than 24 bronze?

Answer: none
[Table] header: Rank | Nation | Gold | Silver | Bronze | Total row 1 : 1 | United States | 26 | 21 | 24 | 71
row 2 : 2 | Norway | 10 | 1 | 2 | 13
row 3 : 3 | East Germany | 9 | 8 | 2 | 19
row 4 : 4 | Austria | 7 | 17 | 12 | 36
row 5 : 5 | Japan | 7 | 3 | 6 | 16
row 6 : 6 | Hungary | 7 | 1 | 3 | 11
row 7 : 7 | Great Britain | 6 | 9 | 7 | 22
row 8 : 8 | Canada | 4 | 5 | 4 | 13
row 9 : 9 | Netherlands | 4 | 1 | 3 | 8
row 10 : 10 | Russia | 3 | 5 | 4 | 12
row 11 : 11 | South Korea | 2 | 2 | 2 | 6
row 12 : 12 | Czechoslovakia | 2 | 0 | 3 | 5
row 13 : 13 | Germany | 1 | 8 | 4 | 13
row 14 : 14 | France | 1 | 4 | 2 | 7
row 15 : 15 | Italy | 1 | 2 | 3 | 6
row 16 : 16 | China | 1 | 1 | 2 | 4
row 17 : 17 | Switzerland | 1 | 0 | 0 | 1
row 18 : 17 | Ukraine | 1 | 0 | 0 | 1
row 19 : 19 | Sweden | 0 | 2 | 5 | 7
row 20 : 20 | Soviet Union | 0 | 2 | 1 | 3
row 21 : 21 | Finland | 0 | 0 | 1 | 1 [/Table] Answer this question based on the above table: What is the sum of Bronze when the rank is 7, and the total is more than 22?

Answer: none
[Table] header: Rank | Nation | Gold | Silver | Bronze | Total row 1 : 1 | United States | 26 | 21 | 24 | 71
row 2 : 2 | Norway | 10 | 1 | 2 | 13
row 3 : 3 | East Germany | 9 | 8 | 2 | 19
row 4 : 4 | Austria | 7 | 17 | 12 | 36
row 5 : 5 | Japan | 7 | 3 | 6 | 16
row 6 : 6 | Hungary | 7 | 1 | 3 | 11
row 7 : 7 | Great Britain | 6 | 9 | 7 | 22
row 8 : 8 | Canada | 4 | 5 | 4 | 13
row 9 : 9 | Netherlands | 4 | 1 | 3 | 8
row 10 : 10 | Russia | 3 | 5 | 4 | 12
row 11 : 11 | South Korea | 2 | 2 | 2 | 6
row 12 : 12 | Czechoslovakia | 2 | 0 | 3 | 5
row 13 : 13 | Germany | 1 | 8 | 4 | 13
row 14 : 14 | France | 1 | 4 | 2 | 7
row 15 : 15 | Italy | 1 | 2 | 3 | 6
row 16 : 16 | China | 1 | 1 | 2 | 4
row 17 : 17 | Switzerland | 1 | 0 | 0 | 1
row 18 : 17 | Ukraine | 1 | 0 | 0 | 1
row 19 : 19 | Sweden | 0 | 2 | 5 | 7
row 20 : 20 | Soviet Union | 0 | 2 | 1 | 3
row 21 : 21 | Finland | 0 | 0 | 1 | 1 [/Table] Answer this question based on the above table: What is the sum of rank when silver is 1, and gold is less than 7, and bronze is 2?

Answer: 16.0
[Table] header: Year | Production | Composer | Conductor | Director row 1 : 2014 | The Snowmaiden [ citation needed ] | Rimsky-Korsakov | Charles Peebles | Christopher Cowell
row 2 : 2013 | I Lombardi | Verdi | Charles Peebles | Jamie Hayes
row 3 : 2012 | Acante et Céphise | Rameau | Charles Peebles | Christopher Cowell
row 4 : 2011 | The Three Pintos (Die Drei Pinto | Weber / Mahler | Charles Peebles | John Ramster
row 5 : 2010 | Genoveva | Schumann | Charles Peebles | Emma Rivlin
row 6 : 2009 | Macbeth * | Bloch | Charles Peebles | John Ramster
row 7 : 2008 | Fiesque * | Lalo | Charles Peebles | Emma Rivlin
row 8 : 2007 | Camacho's Wedding | Mendelssohn | Charles Peebles | Duncan Macfarland
row 9 : 2006 | Alfonso und Estrella | Schubert | Charles Peebles | Stephen Barlow
row 10 : 2005 | Whittington | Offenbach | Charles Peebles | Jamie Hayes
row 11 : 2004 | Vanda * | Dvořák | Charles Peebles | Matthias Janser
row 12 : 2003 | Ciboulette* | Hahn | Charles Peebles | Daniele Guerra
row 13 : 2002 | Benvenuto Cellini | Berlioz | Charles Peebles | Jamie Hayes
row 14 : 2001 | Kullervo* | Sallinen | David Drummond | Paul Curran [/Table] Answer this question based on the above table: Who was the Conductor of the Three Pintos (Die Drei Pintos) Production?

Answer: none
[Table] header: Year | Production | Composer | Conductor | Director row 1 : 2014 | The Snowmaiden [ citation needed ] | Rimsky-Korsakov | Charles Peebles | Christopher Cowell
row 2 : 2013 | I Lombardi | Verdi | Charles Peebles | Jamie Hayes
row 3 : 2012 | Acante et Céphise | Rameau | Charles Peebles | Christopher Cowell
row 4 : 2011 | The Three Pintos (Die Drei Pinto | Weber / Mahler | Charles Peebles | John Ramster
row 5 : 2010 | Genoveva | Schumann | Charles Peebles | Emma Rivlin
row 6 : 2009 | Macbeth * | Bloch | Charles Peebles | John Ramster
row 7 : 2008 | Fiesque * | Lalo | Charles Peebles | Emma Rivlin
row 8 : 2007 | Camacho's Wedding | Mendelssohn | Charles Peebles | Duncan Macfarland
row 9 : 2006 | Alfonso und Estrella | Schubert | Charles Peebles | Stephen Barlow
row 10 : 2005 | Whittington | Offenbach | Charles Peebles | Jamie Hayes
row 11 : 2004 | Vanda * | Dvořák | Charles Peebles | Matthias Janser
row 12 : 2003 | Ciboulette* | Hahn | Charles Peebles | Daniele Guerra
row 13 : 2002 | Benvenuto Cellini | Berlioz | Charles Peebles | Jamie Hayes
row 14 : 2001 | Kullervo* | Sallinen | David Drummond | Paul Curran [/Table] Answer this question based on the above table: Who is the Conductor who had Stephen Barlow as Director?

Answer: Charles Peebles
[Table] header: Year | Production | Composer | Conductor | Director row 1 : 2014 | The Snowmaiden [ citation needed ] | Rimsky-Korsakov | Charles Peebles | Christopher Cowell
row 2 : 2013 | I Lombardi | Verdi | Charles Peebles | Jamie Hayes
row 3 : 2012 | Acante et Céphise | Rameau | Charles Peebles | Christopher Cowell
row 4 : 2011 | The Three Pintos (Die Drei Pinto | Weber / Mahler | Charles Peebles | John Ramster
row 5 : 2010 | Genoveva | Schumann | Charles Peebles | Emma Rivlin
row 6 : 2009 | Macbeth * | Bloch | Charles Peebles | John Ramster
row 7 : 2008 | Fiesque * | Lalo | Charles Peebles | Emma Rivlin
row 8 : 2007 | Camacho's Wedding | Mendelssohn | Charles Peebles | Duncan Macfarland
row 9 : 2006 | Alfonso und Estrella | Schubert | Charles Peebles | Stephen Barlow
row 10 : 2005 | Whittington | Offenbach | Charles Peebles | Jamie Hayes
row 11 : 2004 | Vanda * | Dvořák | Charles Peebles | Matthias Janser
row 12 : 2003 | Ciboulette* | Hahn | Charles Peebles | Daniele Guerra
row 13 : 2002 | Benvenuto Cellini | Berlioz | Charles Peebles | Jamie Hayes
row 14 : 2001 | Kullervo* | Sallinen | David Drummond | Paul Curran [/Table] Answer this question based on the above table: Who was Director John Ramster's Composer?

Answer: Weber / Mahler, Bloch
[Table] header: Season | Overall | Slalom | Giant Slalom | Super G | Downhill | Combined row 1 : 2008 | 54 | — | — | 26 | 30 | —
row 2 : 2009 | 11 | 45 | 9 | 11 | 12 | 16
row 3 : 2010 | injured: out for entire season | injured: out for entire season | injured: out for entire season | injured: out for entire season | injured: out for entire season | injured: out for entire season
row 4 : 2011 | 10 | — | 28 | 4 | 7 | 30
row 5 : 2012 | 14 | — | 17 | 8 | 18 | 30
row 6 : 2013 | 9 | — | 6 | 10 | 5 | 4 [/Table] Answer this question based on the above table: Which Giant Slalom has a Slalom of 45?

Answer: 9.0
[Table] header: Season | Overall | Slalom | Giant Slalom | Super G | Downhill | Combined row 1 : 2008 | 54 | — | — | 26 | 30 | —
row 2 : 2009 | 11 | 45 | 9 | 11 | 12 | 16
row 3 : 2010 | injured: out for entire season | injured: out for entire season | injured: out for entire season | injured: out for entire season | injured: out for entire season | injured: out for entire season
row 4 : 2011 | 10 | — | 28 | 4 | 7 | 30
row 5 : 2012 | 14 | — | 17 | 8 | 18 | 30
row 6 : 2013 | 9 | — | 6 | 10 | 5 | 4 [/Table] Answer this question based on the above table: Which Slalom has a Super G of 4?

Answer: —
[Table] header: Year | Dates | Champion | Country | Score | Margin of victory | Tournament Location | Purse ( US$ ) | Winner's share row 1 : 2013 | Feb 28 – Mar 3 | Stacy Lewis | United States | 273 (−15) | 1 stroke | Sentosa Golf Club | 1,400,000 | 210,000
row 2 : 2012 | Feb 23–26 | Angela Stanford | United States | 278 (−10) | Playoff | Tanah Merah Country Club | 1,400,000 | 210,000
row 3 : 2011 | Feb 24–27 | Karrie Webb | Australia | 275 (−13) | 1 stroke | Tanah Merah Country Club | 1,400,000 | 210,000
row 4 : 2010 | Feb 25–28 | Ai Miyazato | Japan | 278 (−10) | 2 strokes | Tanah Merah Country Club | 1,300,000 | 195,000
row 5 : 2009 | Mar 5–8 | Jiyai Shin | South Korea | 277 (−11) | 2 strokes | Tanah Merah Country Club | 2,000,000 | 300,000
row 6 : 2008 | Feb 28 – Mar 2 | Lorena Ochoa | Mexico | 268 (−20) | 11 strokes | Tanah Merah Country Club | 2,000,000 | 300,000 [/Table] Answer this question based on the above table: Which champion has sentosa golf club as the tournament location?

Answer: Stacy Lewis
[Table] header: Year | Dates | Champion | Country | Score | Margin of victory | Tournament Location | Purse ( US$ ) | Winner's share row 1 : 2013 | Feb 28 – Mar 3 | Stacy Lewis | United States | 273 (−15) | 1 stroke | Sentosa Golf Club | 1,400,000 | 210,000
row 2 : 2012 | Feb 23–26 | Angela Stanford | United States | 278 (−10) | Playoff | Tanah Merah Country Club | 1,400,000 | 210,000
row 3 : 2011 | Feb 24–27 | Karrie Webb | Australia | 275 (−13) | 1 stroke | Tanah Merah Country Club | 1,400,000 | 210,000
row 4 : 2010 | Feb 25–28 | Ai Miyazato | Japan | 278 (−10) | 2 strokes | Tanah Merah Country Club | 1,300,000 | 195,000
row 5 : 2009 | Mar 5–8 | Jiyai Shin | South Korea | 277 (−11) | 2 strokes | Tanah Merah Country Club | 2,000,000 | 300,000
row 6 : 2008 | Feb 28 – Mar 2 | Lorena Ochoa | Mexico | 268 (−20) | 11 strokes | Tanah Merah Country Club | 2,000,000 | 300,000 [/Table] Answer this question based on the above table: What is the highest winner's share that has jiyai shin as the championship with a year prior to 2009?

Answer: none
[Table] header: Year | Dates | Champion | Country | Score | Margin of victory | Tournament Location | Purse ( US$ ) | Winner's share row 1 : 2013 | Feb 28 – Mar 3 | Stacy Lewis | United States | 273 (−15) | 1 stroke | Sentosa Golf Club | 1,400,000 | 210,000
row 2 : 2012 | Feb 23–26 | Angela Stanford | United States | 278 (−10) | Playoff | Tanah Merah Country Club | 1,400,000 | 210,000
row 3 : 2011 | Feb 24–27 | Karrie Webb | Australia | 275 (−13) | 1 stroke | Tanah Merah Country Club | 1,400,000 | 210,000
row 4 : 2010 | Feb 25–28 | Ai Miyazato | Japan | 278 (−10) | 2 strokes | Tanah Merah Country Club | 1,300,000 | 195,000
row 5 : 2009 | Mar 5–8 | Jiyai Shin | South Korea | 277 (−11) | 2 strokes | Tanah Merah Country Club | 2,000,000 | 300,000
row 6 : 2008 | Feb 28 – Mar 2 | Lorena Ochoa | Mexico | 268 (−20) | 11 strokes | Tanah Merah Country Club | 2,000,000 | 300,000 [/Table] Answer this question based on the above table: Which county has 2011 as the year?

Answer: Australia
[Table] header: Year | Dates | Champion | Country | Score | Margin of victory | Tournament Location | Purse ( US$ ) | Winner's share row 1 : 2013 | Feb 28 – Mar 3 | Stacy Lewis | United States | 273 (−15) | 1 stroke | Sentosa Golf Club | 1,400,000 | 210,000
row 2 : 2012 | Feb 23–26 | Angela Stanford | United States | 278 (−10) | Playoff | Tanah Merah Country Club | 1,400,000 | 210,000
row 3 : 2011 | Feb 24–27 | Karrie Webb | Australia | 275 (−13) | 1 stroke | Tanah Merah Country Club | 1,400,000 | 210,000
row 4 : 2010 | Feb 25–28 | Ai Miyazato | Japan | 278 (−10) | 2 strokes | Tanah Merah Country Club | 1,300,000 | 195,000
row 5 : 2009 | Mar 5–8 | Jiyai Shin | South Korea | 277 (−11) | 2 strokes | Tanah Merah Country Club | 2,000,000 | 300,000
row 6 : 2008 | Feb 28 – Mar 2 | Lorena Ochoa | Mexico | 268 (−20) | 11 strokes | Tanah Merah Country Club | 2,000,000 | 300,000 [/Table] Answer this question based on the above table: How many winner's shares have ai miyazato as the champion?

Answer: 195000.0
[Table] header: Rank | Nation | Gold | Silver | Bronze | Total row 1 : 1 | Japan | 3 | 3 | 1 | 7
row 2 : 2 | Netherlands | 1 | 0 | 1 | 2
row 3 : 3 | Soviet Union | 0 | 1 | 2 | 3
row 4 : 4 | South Korea | 0 | 0 | 2 | 2
row 5 : 5 | Canada | 0 | 0 | 1 | 1
row 6 : 5 | United States | 0 | 0 | 1 | 1 [/Table] Answer this question based on the above table: What is the total sum of bronze medals for the Soviet Union when there are more than 0 silver medals and more than 3 total medals?

Answer: none
[Table] header: Rank | Nation | Gold | Silver | Bronze | Total row 1 : 1 | Japan | 3 | 3 | 1 | 7
row 2 : 2 | Netherlands | 1 | 0 | 1 | 2
row 3 : 3 | Soviet Union | 0 | 1 | 2 | 3
row 4 : 4 | South Korea | 0 | 0 | 2 | 2
row 5 : 5 | Canada | 0 | 0 | 1 | 1
row 6 : 5 | United States | 0 | 0 | 1 | 1 [/Table] Answer this question based on the above table: What is the lowest rank of a nation with fewer than 3 gold medals, more than 2 bronze medals, and 0 silver medals?

Answer: none
[Table] header: Year | Band | Song | Album | Contribution row 1 : 2004 | Error | --- whole EP --- | Error (EP) | vocals
row 2 : 2008 | Genghis Tron | "The Feast" | Board Up the House | vocals
row 3 : 2008 | A Static Lullaby | "The Pledge" | Rattlesnake! | vocals
row 4 : 2009 | Prong | "Bad Fall" | Power of the Damn Mixxxer | remix
row 5 : 2009 | Every Time I Die | "The Marvelous Slut" | New Junk Aesthetic | vocals
row 6 : 2010 | Soulfly | "Rise of the Fallen" | Omen | vocals
row 7 : 2011 | Architects | "Year In Year Out" | The Here and Now | vocals
row 8 : 2011 | The Devin Townsend Project | "The Mighty Masturbator" | Deconstruction | vocals
row 9 : 2012 | MixHell | "Exit Wound" | "Exit Wound (EP)" | vocals [/Table] Answer this question based on the above table: For the album Board Up the House, what is the contribution?

Answer: vocals
[Table] header: Year | Band | Song | Album | Contribution row 1 : 2004 | Error | --- whole EP --- | Error (EP) | vocals
row 2 : 2008 | Genghis Tron | "The Feast" | Board Up the House | vocals
row 3 : 2008 | A Static Lullaby | "The Pledge" | Rattlesnake! | vocals
row 4 : 2009 | Prong | "Bad Fall" | Power of the Damn Mixxxer | remix
row 5 : 2009 | Every Time I Die | "The Marvelous Slut" | New Junk Aesthetic | vocals
row 6 : 2010 | Soulfly | "Rise of the Fallen" | Omen | vocals
row 7 : 2011 | Architects | "Year In Year Out" | The Here and Now | vocals
row 8 : 2011 | The Devin Townsend Project | "The Mighty Masturbator" | Deconstruction | vocals
row 9 : 2012 | MixHell | "Exit Wound" | "Exit Wound (EP)" | vocals [/Table] Answer this question based on the above table: What band has a year above 2011?

Answer: MixHell
[Table] header: Week | Date | Time ( ET ) | Opponent | Result | Record | Game site row 1 : 1 | September 7, 2008 | 1:00 P.M. | at Baltimore Ravens | L 17–10 | 0–1–0 | M&T Bank Stadium
row 2 : 2 | September 14, 2008 | 1:00 P.M. | Tennessee Titans | L 24–7 | 0–2–0 | Paul Brown Stadium
row 3 : 3 | September 21, 2008 | 1:00 P.M. | at New York Giants | L 26–23 | 0–3–0 | Giants Stadium
row 4 : 4 | September 28, 2008 | 1:00 P.M. | Cleveland Browns | L 20–12 | 0–4–0 | Paul Brown Stadium
row 5 : 5 | October 5, 2008 | 4:15 P.M. | at Dallas Cowboys | L 31–22 | 0–5–0 | Texas Stadium
row 6 : 6 | October 12, 2008 | 1:00 P.M. | at New York Jets | L 26–14 | 0–6–0 | Giants Stadium
row 7 : 7 | October 19, 2008 | 1:00 P.M. | Pittsburgh Steelers | L 38–10 | 0–7–0 | Paul Brown Stadium
row 8 : 8 [a ] | October 26, 2008 | 4:05 P.M. | at Houston Texans | L 35–6 | 0–8–0 | Reliant Stadium
row 9 : 9 | November 2, 2008 | 1:00 P.M. | Jacksonville Jaguars | W 21–19 | 1–8–0 | Paul Brown Stadium
row 10 : 10 [a ] | Bye week | Bye week | Bye week | Bye week | Bye week | Bye week
row 11 : 11 | November 16, 2008 | 1:00 P.M. | Philadelphia Eagles | T 13–13 (OT) | 1–8–1 | Paul Brown Stadium
row 12 : 12 | November 20, 2008 | 8:15 P.M. | at Pittsburgh Steelers | L 27–10 | 1–9–1 | Heinz Field
row 13 : 13 | November 30, 2008 | 1:00 P.M. | Baltimore Ravens | L 34–3 | 1–10–1 | Paul Brown Stadium
row 14 : 14 | December 7, 2008 | 1:00 P.M. | at Indianapolis Colts | L 35–3 | 1–11–1 | Lucas Oil Stadium
row 15 : 15 | December 14, 2008 | 1:00 P.M. | Washington Redskins | W 20–13 | 2–11–1 | Paul Brown Stadium
row 16 : 16 | December 21, 2008 | 1:00 P.M. | at Cleveland Browns | W 14–0 | 3–11–1 | Cleveland Browns Stadium
row 17 : 17 | December 28, 2008 | 1:00 P.M. | Kansas City Chiefs | W 16–6 | 4–11–1 | Paul Brown Stadium [/Table] Answer this question based on the above table: What time was the game played that had a record of 0–2–0?

Answer: 1:00 P.M.