index
int64 1
3M
| question
stringclasses 382
values | hint
stringclasses 98
values | A
stringlengths 1
460
| B
stringlengths 1
460
| C
stringlengths 1
460
| D
stringlengths 1
460
| answer
stringclasses 4
values | category
stringclasses 20
values | image
imagewidth (px) 55
512
| source
stringclasses 569
values | l2-category
stringclasses 6
values | comment
stringclasses 180
values | split
stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1,209 | What will happen next? | nan | the car is gonna crash into the house | the car is gonna fly | the car is gonna drive backwards | both A,B, and C | A | future_prediction | https://www.youtube.com/watch?v=w6urQm7Prs22 | logic_reasoning | nan | dev |
|
1,210 | What will happen next? | nan | the wave is gonna hit the two girls | the wave is gonna go back to the sea | the two girls are gonna swim in the wave | both A,B, and C | A | future_prediction | https://www.youtube.com/watch?v=w6urQm7Prs24 | logic_reasoning | nan | dev |
|
1,211 | What will happen next? | nan | the motorcycle is gonna turn left | the motorcycle is gonna crash into the car | the motorcycle is gonna turn left | both A,B, and C | B | future_prediction | https://www.youtube.com/watch?v=w6urQm7Prs25 | logic_reasoning | nan | dev |
|
1,212 | What will happen next? | nan | the girls is gonna turn the pan around | the pan itself is gonna fly into the woman's face | nothing is gonna happen | both A,B, and C | B | future_prediction | https://www.youtube.com/watch?v=w6urQm7Prs26 | logic_reasoning | nan | dev |
|
1,213 | What will happen next? | nan | they are gonna kiss on the glass door | they are gonna crash the glass door | they are gonna enter the glass door | both A,B, and C | B | future_prediction | https://www.youtube.com/watch?v=w6urQm7Prs27 | logic_reasoning | nan | dev |
|
1,214 | What will happen next? | nan | the truck is gonna turn left | the truck is gonna drive straight forward | the truck is gonna turn over | both A,B, and C | C | future_prediction | https://www.youtube.com/watch?v=w6urQm7Prs28 | logic_reasoning | nan | dev |
|
1,215 | What will happen next? | nan | the boat is gonna crash | the man is gonna keep surfing | the man is gonna fall on the beach | both A,B, and C | C | future_prediction | https://www.youtube.com/watch?v=w6urQm7Prs29 | logic_reasoning | nan | dev |
|
1,217 | What will happen next? | nan | the puppy is gonna bite the man | the puppy is gonna kiss the man | the puppy is gonna sit on the man | both A,B, and C | A | future_prediction | https://www.youtube.com/watch?v=w6urQm7Prs31 | logic_reasoning | nan | dev |
|
1,218 | What will happen next? | nan | the person is gonna fart on the dog | the dog is gonna bite the person | the dog is gonna sleep | both A,B, and C | A | future_prediction | https://www.youtube.com/watch?v=w6urQm7Prs32 | logic_reasoning | nan | dev |
|
1,219 | What will happen next? | nan | the person is gonna fall off the ladder | the person is gonna stand still on the ladder | someone is gonna come and hold the ladder | both A,B, and C | A | future_prediction | https://www.youtube.com/watch?v=w6urQm7Prs33 | logic_reasoning | nan | dev |
|
1,221 | What will happen next? | nan | the kid is gonna slide through | the kid is gonna crash into the other kid | the other kid is gonna dodge | both A,B, and C | B | future_prediction | https://www.youtube.com/watch?v=w6urQm7Prs35 | logic_reasoning | nan | dev |
|
1,222 | What will happen next? | nan | the man is gonna run over | the man is gonna fall | the man is gonna slide along | both A,B, and C | B | future_prediction | https://www.youtube.com/watch?v=w6urQm7Prs36 | logic_reasoning | nan | dev |
|
1,224 | What will happen next? | nan | the man is gonna put down the weight | the man is gonna lift up the weight | the man is gonna fall | both A,B, and C | C | future_prediction | https://www.youtube.com/watch?v=w6urQm7Prs38 | logic_reasoning | nan | dev |
|
1,226 | What will happen next? | nan | the food is gonna fall off the spoon | the woman is gonna feed the baby | the woman is gonna eat the food herself | both A,B, and C | A | future_prediction | https://www.youtube.com/watch?v=w6urQm7Prs40 | logic_reasoning | nan | dev |
|
1,227 | What will happen next? | nan | the woman is gonna grab the suitcase | the suitcase is gonna fall off the escalator | the suitcase is gonna stay still | both A,B, and C | B | future_prediction | https://www.youtube.com/watch?v=w6urQm7Prs41 | logic_reasoning | nan | dev |
|
1,229 | What will happen next? | nan | they are gonna fall off the motorcycle | they are gonna keep driving forward | they are gonna drive backwards | both A,B, and C | A | future_prediction | https://www.youtube.com/watch?v=w6urQm7Prs43 | logic_reasoning | nan | dev |
|
1,230 | What will happen next? | nan | the man is gonna walk back | the man is gonna fall | the man is gonna get up | both A,B, and C | B | future_prediction | https://www.youtube.com/watch?v=w6urQm7Prs44 | logic_reasoning | nan | dev |
|
1,544 | The object shown in this figure: | nan | Is a colorless liquid with a sharp odor | Can be used as a fertilizer for plants | Has a pH value of less than 7 | None of these options are correct. | A | physical_property_reasoning | http://24236290.s21i.faiusr.com/2/ABUIABACGAAgj5fcnwYo8I-c-gIwoAY4oAY.jpg | attribute_reasoning | nan | dev |
|
1,545 | The object shown in this figure: | nan | Is a colorless and odorless gas | Has a boiling point of -161°C | Is a greenhouse gas that contributes to climate change | None of these options are correct. | A | physical_property_reasoning | attribute_reasoning | nan | dev |
||
1,546 | The object shown in this figure: | nan | Is a lustrous, silver-colored metal | Has a density lower than that of aluminum | Is highly resistant to corrosion in seawater and chlorine | None of these options are correct. | C | physical_property_reasoning | http://www.dayueti.com/uploads/allimg/200330/1-200330222436.jpg | attribute_reasoning | nan | dev |
|
1,547 | The object shown in this figure: | nan | Is a colorless liquid with a sweet, fruity odor | Has a boiling point of 56.05°C | Is used as a solvent for many organic compounds | None of these options are correct. | C | physical_property_reasoning | nan | attribute_reasoning | nan | dev |
|
1,548 | The object shown in this figure: | nan | Is a white, odorless powder | Has a relatively low melting point of 825°C | Is the main component of chalk and limestone | None of these options are correct. | C | physical_property_reasoning | http://t15.baidu.com/it/u=2995311842,2565462334&fm=224&app=112&f=JPEG?w=500&h=500 | attribute_reasoning | nan | dev |
|
1,549 | The object shown in this figure: | nan | Is a colorless gas with a slightly sweet odor | Is also known as laughing gas | Has a boiling point of -88.5°C | None of these options are correct. | B | physical_property_reasoning | https://pic.baike.soso.com/ugc/baikepic2/9611/20220314140719-1734772453_png_678_468_305158.jpg/0 | attribute_reasoning | nan | dev |
|
1,550 | The object shown in this figure: | nan | Is a highly corrosive liquid | Has a boiling point of 337°C | Is used to make many types of fertilizers | None of these options are correct. | A | physical_property_reasoning | https://img0.baidu.com/it/u=3181099851,3965974851&fm=253&fmt=auto&app=138&f=JPEG?w=500&h=528 | attribute_reasoning | nan | dev |
|
1,551 | The object shown in this figure: | nan | Is a colorless liquid with a slightly metallic taste | Is a powerful oxidizer that can cause skin and eye irritation | Has a boiling point of 150.2°C | None of these options are correct. | B | physical_property_reasoning | https://img1.baidu.com/it/u=3106915301,4272227426&fm=253&fmt=auto&app=138&f=JPEG?w=322&h=499 | attribute_reasoning | nan | dev |
|
1,552 | The object shown in this figure: | nan | Is a colorless gas with a pungent odor | Is commonly used as a fertilizer and industrial chemical | Has a boiling point of -33.3°C | None of these options are correct. | A | physical_property_reasoning | https://img1.baidu.com/it/u=381738452,98971456&fm=253&fmt=auto&app=138&f=JPEG?w=549&h=410 | attribute_reasoning | nan | dev |
|
1,553 | The gas shown in this figure: | nan | Is a colorless, odorless gas that is poisonous to humans and animals | Forms when fuels like gasoline, coal, and wood are burned without enough oxygen | Has a boiling point of -191.5°C | None of these options are correct. | A | physical_property_reasoning | attribute_reasoning | nan | dev |
||
1,554 | The object shown in this figure: | nan | Is a colorless, flammable liquid that is commonly used as a solvent and fuel | Has a boiling point of 64.7°C | Can be toxic if ingested or absorbed through the skin | None of these options are correct. | C | physical_property_reasoning | https://img1.baidu.com/it/u=4162081172,2358319258&fm=253&fmt=auto&app=138&f=JPEG?w=500&h=694 | attribute_reasoning | nan | dev |
|
1,555 | The object shown in this figure: | nan | Is a lustrous, white metal that is highly reflective and ductile | Has the highest electrical and thermal conductivity of all metals | Has a boiling point of 2,162°C | All of these options are correct. | D | physical_property_reasoning | https://img2.baidu.com/it/u=525544144,463390017&fm=253&fmt=auto&app=138&f=JPEG?w=596&h=500 | attribute_reasoning | nan | dev |
|
1,557 | The object shown in this figure: | nan | Is a type of clathrate compound that consists of methane gas trapped within a lattice of ice crystals | Occurs naturally in deep-sea sediments and permafrost regions | Can be used as a potential energy source | None of these options are correct. | C | physical_property_reasoning | attribute_reasoning | nan | dev |
||
1,561 | The object shown in this figure: | nan | Is a mineral that occurs in many different forms and colors | Has a high melting point of around 1,650°C | Is commonly used in many industrial applications, including electronics and optics | All of these options are correct. | D | physical_property_reasoning | https://bkimg.cdn.bcebos.com/pic/f3d3572c11dfa9ecc9c0b89869d0f703908fc157 | attribute_reasoning | nan | dev |
|
1,563 | The object shown in this figure: | nan | Is a compound made up of silicon and carbon atoms | Is used as an abrasive and cutting tool material | Melts at around 2,730°C | All of these options are correct. | D | physical_property_reasoning | https://bkimg.cdn.bcebos.com/pic/c8177f3e6709c93d70cf69e8cc76efdcd100baa1fed3 | attribute_reasoning | nan | dev |
|
1,564 | The object shown in this figure: | nan | Is a white solid that is commonly used as a pigment and sunscreen ingredient | Has a high melting point of around 1,843°C | Can be produced in both powder and nanoparticle forms | All of these options are correct. | D | physical_property_reasoning | https://gimg2.baidu.com/image_search/src=http%3A%2F%2Fcbu01.alicdn.com%2Fimg%2Fibank%2F2020%2F487%2F879%2F18090978784_2082016289.jpg&refer=http%3A%2F%2Fcbu01.alicdn.com&app=2002&size=f9999,10000&q=a80&n=0&g=0n&fmt=auto?sec=1689837198&t=98bc4a671c9ce72518fc11ee5fb1896e | attribute_reasoning | nan | dev |
|
1,566 | The object shown in this figure: | nan | Is a thermoplastic material that is commonly used in packaging and plastic bags | Has a high molecular weight, making it strong and durable | Melts at around 115-135°C | All of these options are correct. | D | physical_property_reasoning | attribute_reasoning | nan | dev |
||
1,567 | The object shown in this figure: | nan | Is a bluish-white metal that is commonly used in galvanizing and as an alloy in brass and other metals | Has a relatively low melting point of around 419°C | Is an essential micronutrient for humans and many other organisms | All of these options are correct. | D | physical_property_reasoning | attribute_reasoning | nan | dev |
||
1,568 | The object shown in this figure: | nan | Is an amorphous solid that is made by heating silica and other materials to high temperatures | Has many useful properties, including transparency, hardness, and resistance to chemical attack | Does not have a distinct melting point, but softens gradually as it is heated | All of these options are correct. | D | physical_property_reasoning | attribute_reasoning | nan | dev |
||
1,569 | The object shown in this figure: | nan | Is a metallic element that is essential for life and commonly used in construction and manufacturing | Has a relatively low melting point of around 1,538°C | Is the most abundant element by mass in Earth's core | All of these options are correct. | D | physical_property_reasoning | https://img0.baidu.com/it/u=1069165377,1159167237&fm=253&fmt=auto&app=138&f=JPEG?w=750&h=500 | attribute_reasoning | nan | dev |
|
1,570 | The object shown in this figure: | nan | Is a form of carbon that is commonly used as a pigment and reinforcing filler in rubber and other materials | Has a very low reflectivity, making it useful in some electronic displays | Melts at around 3,500°C under high pressure | All of these options are correct. | D | physical_property_reasoning | attribute_reasoning | nan | dev |
||
1 | What is correct Python code to generate the content of the image? | nan | for x in range(6):\n print(x)\nelse:\n print("Finally finished!")\n | thisdict = {\n "brand": "Ford",\n "model": "Mustang",\n "year": 1964\n}\n\nprint(len(thisdict)) | x = 1\ny = 2.8\nz = 1j\n\nprint(type(x))\nprint(type(y))\nprint(type(z))\n | fruits = ["apple", "banana", "cherry"]\nfor x in fruits:\n print(x) | D | structuralized_imagetext_understanding | code | logic_reasoning | nan | dev |
|
2 | What is correct Python code to generate the content of the image? | nan | class Person:\n def __init__(self, name, age):\n self.name = name\n self.age = age\n\np1 = Person("John", 36)\n\nprint(p1.name)\nprint(p1.age) | fruits = ["apple", "banana", "cherry"]\nfor x in fruits:\n print(x) | x = min(5, 10, 25)\ny = max(5, 10, 25)\n\nprint(x)\nprint(y) | a = 33\nb = 200\nif b > a:\n print("b is greater than a") | D | structuralized_imagetext_understanding | code | logic_reasoning | nan | dev |
|
7 | What is correct Python code to generate the content of the image? | nan | x = lambda a, b, c: a + b + c\nprint(x(5, 6, 2))\n | class Person:\n def __init__(self, name, age):\n self.name = name\n self.age = age\n\np1 = Person("John", 36)\n\nprint(p1.name)\nprint(p1.age) | x = lambda a, b: a * b\nprint(x(5, 6))\n | a = """Lorem ipsum dolor sit amet,\nconsectetur adipiscing elit,\nsed do eiusmod tempor incididunt\nut labore et dolore magna aliqua."""\nprint(a)\n | B | structuralized_imagetext_understanding | code | logic_reasoning | nan | dev |
|
8 | What is correct Python code to generate the content of the image? | nan | class Person:\n def __init__(self, fname, lname):\n self.firstname = fname\n self.lastname = lname\n\n def printname(self):\n print(self.firstname, self.lastname)\n\n#Use the Person class to create an object, and then execute the printname method:\n\nx = Person("John", "Doe")\nx.printname()\n | mystr = "banana"\nmyit = iter(mystr)\n\nprint(next(myit))\nprint(next(myit))\nprint(next(myit))\nprint(next(myit))\nprint(next(myit))\nprint(next(myit)) | def my_function():\n print("Hello from a function")\n \nmy_function()\n | x = min(5, 10, 25)\ny = max(5, 10, 25)\n\nprint(x)\nprint(y) | A | structuralized_imagetext_understanding | code | logic_reasoning | nan | dev |
|
9 | What is correct Python code to generate the content of the image? | nan | fruits = ["apple", "banana", "cherry"]\nfor x in fruits:\n print(x) | mystr = "banana"\nmyit = iter(mystr)\n\nprint(next(myit))\nprint(next(myit))\nprint(next(myit))\nprint(next(myit))\nprint(next(myit))\nprint(next(myit)) | i = 1\nwhile i < 6:\n print(i)\n i += 1\n | x = lambda a, b: a * b\nprint(x(5, 6))\n | B | structuralized_imagetext_understanding | code | logic_reasoning | nan | dev |
|
11 | What is correct Python code to generate the content of the image? | nan | def myfunc():\n x = 300\n def myinnerfunc():\n print(x)\n myinnerfunc()\n\nmyfunc() | thisdict = {\n "brand": "Ford",\n "model": "Mustang",\n "year": 1964\n}\n\nprint(len(thisdict)) | x = min(5, 10, 25)\ny = max(5, 10, 25)\n\nprint(x)\nprint(y) | class Person:\n def __init__(self, name, age):\n self.name = name\n self.age = age\n\np1 = Person("John", 36)\n\nprint(p1.name)\nprint(p1.age) | A | structuralized_imagetext_understanding | code | logic_reasoning | nan | dev |
|
12 | What is correct Python code to generate the content of the image? | nan | x = lambda a, b, c: a + b + c\nprint(x(5, 6, 2))\n | x = min(5, 10, 25)\ny = max(5, 10, 25)\n\nprint(x)\nprint(y) | class Person:\n def __init__(self, name, age):\n self.name = name\n self.age = age\n\np1 = Person("John", 36)\n\nprint(p1.name)\nprint(p1.age) | i = 1\nwhile i < 6:\n print(i)\n i += 1\n | B | structuralized_imagetext_understanding | code | logic_reasoning | nan | dev |
|
16 | What is correct Python code to generate the content of the image? | nan | def my_function(fname, lname):\n print(fname + " " + lname)\n\nmy_function("Emil", "Refsnes")\n | x = int(1)\ny = int(2.8)\nz = int("3")\nprint(x)\nprint(y)\nprint(z)\n | i = 1\nwhile i < 6:\n print(i)\n i += 1\n | class Person:\n def __init__(self, fname, lname):\n self.firstname = fname\n self.lastname = lname\n\n def printname(self):\n print(self.firstname, self.lastname)\n\n#Use the Person class to create an object, and then execute the printname method:\n\nx = Person("John", "Doe")\nx.printname()\n | A | structuralized_imagetext_understanding | code | logic_reasoning | nan | dev |
|
18 | What is correct Python code to generate the content of the image? | nan | x = 1\ny = 2.8\nz = 1j\n\nprint(type(x))\nprint(type(y))\nprint(type(z))\n | print(10 > 9)\nprint(10 == 9)\nprint(10 < 9)\n | x = lambda a: a + 10\nprint(x(5)) | x = 1.10\ny = 1.0\nz = -35.59\n\nprint(type(x))\nprint(type(y))\nprint(type(z))\n | B | structuralized_imagetext_understanding | code | logic_reasoning | nan | dev |
|
21 | Which one is the correct caption of this image? | nan | A man rides a surfboard on a large wave. | a young boy barefoot holding an umbrella touching the horn of a cow | A giraffe standing by a stall in a field. | A stop sign that has been vandalized with graffiti. | B | action_recognition | description | finegrained_perception (cross-instance) | nan | dev |
|
22 | Which one is the correct caption of this image? | nan | A narrow kitchen filled with appliances and cooking utensils. | A person with glasses and a tie in a room. | Tray of vegetables with cucumber, carrots, broccoli and celery. | A pretty young woman riding a surfboard on a wave in the ocean. | A | image_scene | description | coarse_perception | nan | dev |
|
24 | Which one is the correct caption of this image? | nan | A commercial kitchen with pots several pots on the stove. | a shower a toilet some toilet paper and rugs | A pizza covered in lots of greens on top of a table. | A toilet in a bathroom with green faded paint. | D | object_localization | description | finegrained_perception (instance-level) | nan | dev |
|
25 | Which one is the correct caption of this image? | nan | A chocolate cake with icing next to plates and spoons. | Stuffed teddy bear sitting next to garbage can on the side of the road. | A group of baseball players playing a game of baseball. | Two stainless steel sinks with mirrors and a fire extinguisher. | D | object_localization | description | finegrained_perception (instance-level) | nan | dev |
|
27 | Which one is the correct caption of this image? | nan | A parking meter sign points to where the meter is | A woman is walking across a wooden bridge with a surfboard. | A picture of a vase of flowers on a shelf. | A bathroom with multicolored tile, bathtub and pedestal sink. | D | image_scene | description | coarse_perception | nan | dev |
|
28 | Which one is the correct caption of this image? | nan | A series of parking meters and cars are located next to each other. | A person sitting on a bench with lots of written signs. | A sad woman laying on a mattress on a hardwood floor. | A large long train on a steel track. | A | image_scene | description | coarse_perception | nan | dev |
|
30 | Which one is the correct caption of this image? | nan | A toilet sitting in an outdoor area with a helmet resting on top of it. | five unopened umbrellas on a sand bar reflecting in water | A man preparing a vegetable plates for consumption. | A simple bathroom with a toilet and shower. | A | image_scene | description | coarse_perception | nan | dev |
|
38 | Which one is the correct caption of this image? | nan | A plane sitting on a runway getting ready to be emptied. | Children playing soccer in a field with other children. | A man taking a selfie between two mirrors | Man on skateboard with long stick in front of slotted building | A | image_topic | description | coarse_perception | nan | dev |
|
45 | Which one is the correct caption of this image? | nan | A brown teddy bear is laying on a bed. | A giraffe lying on the ground in a zoo pin. | Two men and a dog in a kitchen. | a cat standing on the edge of a toilet bowl with its front paws inside of the toilet. | B | image_scene | description | coarse_perception | nan | dev |
|
46 | Which one is the correct caption of this image? | nan | A black and white cat in front of a laptop and a monitor. | A man wearing a suit and maroon tie smiles at other people. | A photo of an organized bathroom pulls from the black window trim. | A couple of giraffes that are standing in the grass. | D | image_scene | description | coarse_perception | nan | dev |
|
47 | Which one is the correct caption of this image? | nan | People in a horse drawn buggy on a city street. | A fire hydrant with a pair of eye stickers making a face on it. | a large food truck is parked on the side of the street | Neither one of these people had a good flight. | B | image_scene | description | coarse_perception | nan | dev |
|
48 | Which one is the correct caption of this image? | nan | A red fire hydrant spouting water onto sidewalk with trees in background. | The bench is empty but the birds enjoy their alone time. | a clock on a pole on a city street | Three boys posing with their helmets on and their bikes. | A | image_scene | description | coarse_perception | nan | dev |
|
49 | Which one is the correct caption of this image? | nan | a woman a sign and a tan teddy bear | An old building with a steeple and two clocks is surrounded by gray clouds. | a girl in shorts and shoes kicking a soccer ball in a stadium | A yellow and blue fire hydrant sitting on a sidewalk. | D | image_scene | description | coarse_perception | nan | dev |
|
50 | Which one is the correct caption of this image? | nan | A triangle sign with an English and foreign warning | Each of the three cakes have icing flowers on them. | A very old antique clock on a wall. | A tv is on in the living room, but no one is in there. | A | image_topic | description | coarse_perception | nan | dev |
|
53 | Which one is the correct caption of this image? | nan | A group of giraffes and zebras in a wildlife exhibit. | A man wearing a black hat while talking on a phone. | An empty kitchen with a window and a refrigerators. | A bowl of bananas sitting on the kitchen table. | A | image_scene | description | coarse_perception | nan | dev |
|
54 | Which one is the correct caption of this image? | nan | A grey and white bird with red feet and eyes perches on a branch. | A broken flip phone sits, in two pieces, on the counter. | pieces of kiwi and peach cut up on a plate next to a teapot | Three small piece of fried food on a white plate with writing. | A | image_topic | description | coarse_perception | nan | dev |
|
55 | Which one is the correct caption of this image? | nan | A man on a skateboard on a concrete lip. | Hand holding an electronic component with a clock on it. | Young woman lying face down on a large bed with a book. | A big billboard is painted onto the side of a brick building. | D | image_scene | description | coarse_perception | nan | dev |
|
57 | Which one is the correct caption of this image? | nan | The street sign at the intersection of Broadway and 7th avenue is the star of this picture. | A black and red Pontiac vehicle with a group of bikes on top of it and people standing near by with umbrellas. | a table of food on a wooden table with two people sitting at it | A body of water with an elephant in the background. | A | image_scene | description | coarse_perception | nan | dev |
|
58 | Which one is the correct caption of this image? | nan | A couple of elephants walking around a body of water. | A red and blue train on a bridge during a cloudy day. | An elephant walking through a lake near land. | A black cat and a black bird in front of a blue door to a red building. | B | image_scene | description | coarse_perception | nan | dev |
|
62 | Which one is the correct caption of this image? | nan | An oven sitting on the concrete outside of a building. | A person is skiing down a snowy mountain. | A small cat is sitting on the wooden beam. | The skaters are trying their tricks on the abandoned street. | C | image_scene | description | coarse_perception | nan | dev |
|
64 | Which one is the correct caption of this image? | nan | A green and grey helicopter in a hazy sky. | A woman with a polka-dotted umbrella and a grey shirt reading a pamphlet. | A blond person is using the toilet and smiling. | A cat and dog napping together on the couch. | D | image_topic | description | coarse_perception | nan | dev |
|
67 | Which one is the correct caption of this image? | nan | A white bathroom sink sitting next to a walk in shower. | a dog in a field with a frisbee in its mouth | A small tower that has a clock at the top. | A furry cat sleeping inside a packed suitcase | D | image_topic | description | coarse_perception | nan | dev |
|
68 | Which one is the correct caption of this image? | nan | Cooked snack item in bread on plate with condiment. | A gray chair and a black chair sit in a room near a lamp. | a stop sign on the corner of a street of apartments | Old Double Decker bus driving through heavy traffic | B | image_topic | description | coarse_perception | nan | dev |
|
69 | Which one is the correct caption of this image? | nan | A close up of a bicycle parked on a train platform. | Cows are walking through tall grass near many trees. | Beautiful silhouette of a woman holding a surfboard at a beach. | A blender, lime, salt, and tequila on a counter. | B | image_scene | description | coarse_perception | nan | dev |
|
70 | Which one is the correct caption of this image? | nan | some clouds a traffic light and some buildings | A man walks through the ocean water with a surfboard under his arm. | A vehicle is shown transporting a shipment of bicycles. | a laptop a mouse a desk and some wires | C | image_scene | description | coarse_perception | nan | dev |
|
72 | Which one is the correct caption of this image? | nan | A woman is cutting up a block of spam. | A man standing near the home plate swinging a bat | An older orange van is parked next to a modern mini van in front of a small shop. | A black kitten laying down next to two remote controls. | D | image_topic | description | coarse_perception | nan | dev |
|
73 | Which one is the correct caption of this image? | nan | THERE ARE A LOT OF DIFFERENT TIES ON THE TABLE | Lots of fruit sits on bowls on the counter of this kitchen. | SEVERAL PEOPLE ARE SKIING AT A SKI RESORT WITH THE MOUNTAINS BEHIND THEM | a nd elephant is carrying some red jugs | D | image_scene | description | coarse_perception | nan | dev |
|
74 | Which one is the correct caption of this image? | nan | an elephant is in some brown grass and some trees | The two pieces of abandoned luggage are waiting to be claimed. | A large polar bear playing with two balls. | A large crowd of people huddling under umbrellas. | A | image_scene | description | coarse_perception | nan | dev |
|
75 | Which one is the correct caption of this image? | nan | A bunch of cars sitting still in the middle of a street | Two giraffes near a tree in the wild. | Small personal bathroom with a tiny entrance door. | An elephant drinking water while the rest of the herd is walking in dry grass. | D | image_scene | description | coarse_perception | nan | dev |
|
78 | Which one is the correct caption of this image? | nan | A woman standing in front of a horse. | A man standing next to a red motorcycle on a stone walkway. | A man is throwing a frisbee in a sandy area. | A mother and son elephant walking through a green grass field. | D | image_scene | description | coarse_perception | nan | dev |
|
82 | Which one is the correct caption of this image? | nan | Five people stand on a shoreline, with woods in the background. | THERE IS A COMMUTER TRAIN ON THE TRACKS | A large city bus is parked on the side of a street. | A man holding a frisbee in the field close to some buildings | A | image_scene | description | coarse_perception | nan | dev |
|
85 | Which one is the correct caption of this image? | nan | Two men playing a game of catch on a street. | A woman sitting on a couch next to a bathroom sink. | A zebra resting its head on another zebra | The bathroom in the cabin needs to be remodeled. | C | action_recognition | description | finegrained_perception (cross-instance) | nan | dev |
|
86 | Which one is the correct caption of this image? | nan | A motorcyclist in full gear posing on his bike. | Someone who is enjoying some nutella on a banana for lunch. | A picture of a dog on a bed. | Person riding on the back of a horse on a gravel road. | D | image_scene | description | coarse_perception | nan | dev |
|
88 | Which one is the correct caption of this image? | nan | Horses behind a fence near a body of water. | a blurry photo of a baseball player holding a bat | The woman in the yellow dress is sitting beside the window | a couple of zebras standing in some grass | A | image_scene | description | coarse_perception | nan | dev |
|
89 | Which one is the correct caption of this image? | nan | A little girl riding a horse next to another girl. | A dark room with chairs and painting of coffee cups on the wall, and a laptop computer in the foreground. | Spectators are watching a snowboard competition of the Olympics. | A house lined road with red trucks on the side of the street | A | image_topic | description | coarse_perception | nan | dev |
|
91 | Which one is the correct caption of this image? | nan | A drivers side rear view mirror on an auto waiting at a red traffic light. | Two horses gaze out from among the trees. | Surfer riding on decent sized wave as it breaks in ocean. | A man in a suite sits at a table. | B | image_scene | description | coarse_perception | nan | dev |
|
92 | Which one is the correct caption of this image? | nan | A standing toilet sitting inside of a stone and cement room. | Two skate boarders and one of them mid-jump. | A wooden table with a white plate of fresh fruit sitting on it. | Three wild goats playing on a rocky mountainside. | C | image_topic | description | coarse_perception | nan | dev |
|
94 | Which one is the correct caption of this image? | nan | A cat that is laying down on a carpet. | A woman standing with a bag in a mirror. | A person dressed in costume, wearing a banana hat and a banana necklace. | Billboard on a commercial street corner in an oriental city | C | image_topic | description | coarse_perception | nan | dev |
|
95 | Which one is the correct caption of this image? | nan | A fork, apple, orange and onion sitting on a surface. | An old adobe mission with a clock tower stands behind a sparsely leaved tree. | A person holding a surfboard on a beach leaning to look at a second surfboard on the sand | Three horses pulling a cart with a man riding it | A | image_topic | description | coarse_perception | nan | dev |
|
97 | Which one is the correct caption of this image? | nan | The clock on the building is in the shape of a coffee cup. | An orange and white kitten sleeping on a wood floor beside a shoe. | A large building on a beach with umbrellas. | a male tennis player in a blue shirt is playing tennis | A | image_topic | description | coarse_perception | nan | dev |
|
99 | Which one is the correct caption of this image? | nan | This empty kitchen has a refrigerator, cabinets, and cupboards. | A slice of cake next to a bottle of cola. | A person riding down a sidewalk on a skateboard. | A tan colored horse is tied to a treadmill. | C | action_recognition | description | finegrained_perception (cross-instance) | nan | dev |
|
100 | Which one is the correct caption of this image? | nan | A bike sitting near the water that has boats in it. | a red double decker bus is seen coming up the street | A motorcycle leaning on a car in street. | A man is eating a hot dog while wearing a suit. | D | action_recognition | description | finegrained_perception (cross-instance) | nan | dev |
|
101 | Which one is the correct caption of this image? | nan | A lone zebra on a cloudy day standing in grass. | A foot long hot dog on top of two buns. | A store room holds sinks, bathtubs and toilets | Two sheep play in the middle of a rocky slope. | B | image_topic | description | coarse_perception | nan | dev |
|
102 | Which one is the correct caption of this image? | nan | A white toilet sitting inside of a bathroom. | A young child is sitting at a bar and eating. | Mother and young black & white cow eating in a field of grass. | A skier wearing a red jacket is jumping in the air. | B | image_topic | description | coarse_perception | nan | dev |
|
107 | Which one is the correct caption of this image? | nan | A brightly colored store front with benches and chairs. | The sun is about set on the beach. | A man holding up what appears to be a chocolate desert. | A view of a close up of a computer. | C | action_recognition | description | finegrained_perception (cross-instance) | nan | dev |
|
108 | Which one is the correct caption of this image? | nan | A man and a young girl playing video games | A baseball pitcher prepares to deliver a pitch. | A birthday cake with candles and a cell phone. | a couple of big airplanes that are in a tunnel | C | image_topic | description | coarse_perception | nan | dev |
|
109 | Which one is the correct caption of this image? | nan | A man looking to his side while he holds his arms up to catch a frisbee. | A traffic sigh stating an area is restricted and no thru traffic is allowed. | A white stove top oven sitting inside of a kitchen. | A group of children running after a soccer ball | D | action_recognition | description | finegrained_perception (cross-instance) | nan | dev |
|
112 | Which one is the correct caption of this image? | nan | A white and red bus is traveling down a road. | There are several pictures of a woman riding a horse at a competition. | A soccer player looks up at a soccer ball. | A cat is laying on top of a laptop computer. | C | action_recognition | description | finegrained_perception (cross-instance) | nan | dev |
|
114 | Which one is the correct caption of this image? | nan | A dirty squat toilet surrounded by white tile. | A street of a Chinese town in the afternoon | A chocolate and fudge dessert on layered pastry is on a red plate. | A row of vehicles sitting at a traffic light on a street. | C | image_topic | description | coarse_perception | nan | dev |
|
115 | Which one is the correct caption of this image? | nan | a messy bed room a bed a chair and boxes | A woman laying in bed next to a large stuffed animal. | A tennis player resting on the floor under a hat. | Odd plant and flower arrangement in a vase. | A | image_scene | description | coarse_perception | nan | dev |
|
116 | Which one is the correct caption of this image? | nan | A man in a wetsuit with a surfboard standing on a beach. | A commuter bus driving throw snowy, slushy weather | A brown duck swims in some brown water. | A sandwich and a salad are on a tray on a wooden table. | A | image_scene | description | coarse_perception | nan | dev |
|
118 | Which one is the correct caption of this image? | nan | You will not get anywhere if you open these doors and try to pass through. | A corner bathtub in a very clean bathroom. | Three men all eating sub sandwiches at a restaurant. | a cat that is drinking out of a sink | C | action_recognition | description | finegrained_perception (cross-instance) | nan | dev |
|
121 | which of the following skills would likely be least important to successfully perform the frisbee trick? | nan | The ability to accurately predict weather conditions. | Having good hand-eye coordination. | Being able to maintain balance. | Having flexibility and dexterity. | A | function_reasoning | reasoning | attribute_reasoning | nan | dev |
Subsets and Splits