index
int64 2
3M
| question
stringclasses 377
values | hint
stringclasses 97
values | answer
stringclasses 4
values | A
stringlengths 1
460
| B
stringlengths 1
460
| C
stringlengths 1
460
| D
stringlengths 1
460
| category
stringclasses 20
values | image
imagewidth (px) 55
512
| source
stringclasses 563
values | L2-category
stringclasses 6
values | comment
stringclasses 177
values | split
stringclasses 1
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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2,001,632 | what python code is gonna generate the result as shown in the image? | nan | C | #This is a comment.
print("Hello, World!") | if 5 > 2:
print("Five is greater than two!") | if 5 > 2:
print("Five is greater than two!")
print("Five is greater than two!") | if 5 > 2:
print("Five is greater than two!")
if 5 > 2:
print("Five is greater than two!") | structuralized_imagetext_understanding | https://www.w3schools.com/python/trypython.asp?filename=demo_indentation2 | logic_reasoning | nan | dev |
|
1,740 | Which operation of fractions is represented by this formula? | nan | A | Add | Subtract | Multiply | Devide | ocr | finegrained_perception (instance-level) | nan | dev |
||
3,000,660 | How many Cows in this picture? | nan | B | one | two | nine | four | object_localization | COCO_test2015 | finegrained_perception (instance-level) | 000000000019.jpg | dev |
|
1,798 | Which of the following captions best describes this image? | nan | B | A person playing a guitar on a stage | A group of people dancing at a party | A singer performing on a microphone | A person playing a piano in a studio | image_scene | coarse_perception | nan | dev |
||
3,001,980 | In nature, what's the relationship between these two creatures? | nan | D | Competitive relationships | Parasitic relationships | Symbiotic relationship | Predatory relationships | nature_relation | https://th.bing.com/th/id/R.7cdab3780771098fbedcdc6798883e07?rik=UyOVb%2bw7U8f5BA&riu=http%3a%2f%2fimg.coozhi.com%2fupload%2f20200615%2f15t9r220u9m23p27cdab3780771098fbedcdc6798883e07.0x750x450.jpg&ehk=%2bTBTz%2fHtKH8eB6e6lfGmyuQej8W1HQnq9H8V3nDEiug%3d&risl=&pid=ImgRaw&r=0 | relation_reasoning | nan | dev |
|
1,000,710 | Extract text from the image | nan | B | USA ARMY | UNITED STATES ARMY | U.S. MILITARY FORCES | AMERICAN LAND TROOPS | ocr | TextVQA test-split | finegrained_perception (instance-level) | 0f739ac580276e5f.jpg | dev |
|
1,001,757 | The area of which figure can be calculated using the formula in this picture? | nan | A | Circle. | Square. | Rectangle. | Triangle. | ocr | finegrained_perception (instance-level) | nan | dev |
||
3,000,109 | Which one is the correct caption of this image? | nan | C | 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 | A man looking to his side while he holds his arms up to catch a frisbee. | action_recognition | description | finegrained_perception (cross-instance) | nan | dev |
|
1,001,391 | What's the profession of the people in this picture? | nan | A | soldier | mason | postman | singer | identity_reasoning | attribute_reasoning | nan | dev |
||
723 | Who is the person in this image? | nan | D | Xiang Liu | Lionel Messi | Morgan Freeman | Elon Musk | celebrity_recognition | Google | finegrained_perception (instance-level) | nan | dev |
|
1,346 | Which mood does this image convey? | nan | A | Sad | Anxious | Happy | Angry | image_emotion | coarse_perception | nan | dev |
||
2,001,598 | what style is depicted in this image? | nan | D | modernism | dadaism | impressionism | post-Impressionism | image_style | coarse_perception | nan | dev |
||
88 | Which one is the correct caption of this image? | nan | A | 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 | image_scene | description | coarse_perception | nan | dev |
|
3,000,025 | Which one is the correct caption of this image? | nan | C | 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. | A chocolate cake with icing next to plates and spoons. | object_localization | description | finegrained_perception (instance-level) | nan | dev |
|
2,001,774 | This picture shows the lesson plan for Mike. Can you tell me what time should Mike learn biology on Wednesday? | nan | B | 13:00-14:30. | 14:45-16:15. | 10:00-11:30. | 11:30-12:30. | structuralized_imagetext_understanding | logic_reasoning | nan | dev |
||
1,001,378 | What's the profession of the people in this picture? | nan | A | doctor | baker | butcher | carpenter | identity_reasoning | attribute_reasoning | nan | dev |
||
2,000,999 | Based on the image, where is the laptop? | nan | D | The laptop is next to the small table | The laptop is next to the bed | The laptop is on the bed | The laptop is on the small table | physical_relation | COCO train2014 | relation_reasoning | 3.png | dev |
|
1,001,347 | Which mood does this image convey? | nan | D | Angry | Sad | Anxious | Happy | image_emotion | coarse_perception | nan | dev |
||
1,842 | What direction is Germany in the Mediterranean Sea? | nan | D | east | south | west | north | spatial_relationship | https://www.google.com/maps/@44.3563054,26.1089918,4z?entry=ttu | finegrained_perception (cross-instance) | nan | dev |
|
515 | Identify the emotion expressed in this image. | nan | A | happiness | sadness | anger | loneliness | image_emotion | Internet | coarse_perception | nan | dev |
|
2,000,970 | Where is it located? | nan | B | Beijing | Xi'an | Chengdu | Canton | celebrity_recognition | https://img1.baidu.com/it/u=406353686,381926990&fm=253&fmt=auto&app=138&f=JPEG?w=750&h=500 | finegrained_perception (instance-level) | 4.png | dev |
|
107 | Which one is the correct caption of this image? | nan | C | 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. | action_recognition | description | finegrained_perception (cross-instance) | nan | dev |
|
1,000,155 | Based on the image, what considerations should be made for the well-being of the horse in the field? | nan | B | The horse should be kept in a small enclosure for safety. | The horse should have access to high-quality forage or hay in addition to the grass. | The horse should be trained for riding purposes. | The horse should have a variety of toys for entertainment. | function_reasoning | reasoning | attribute_reasoning | nan | dev |
|
3,000,568 | This image is an example of which style? | nan | D | comic | oil paint | Baroque | vector art | image_style | Internet | coarse_perception | nan | dev |
|
1,001,951 | In nature, what's the relationship between these two creatures? | nan | B | Symbiotic relationship | Predatory relationships | Competitive relationships | Parasitic relationships | nature_relation | relation_reasoning | nan | dev |
||
2,001,097 | Are the two pens the same size in the picture? | nan | A | Not the same | Can't judge | same | nan | attribute_comparison | https://www.bing.com/images/search?view=detailV2&ccid=tCTjLEY3&id=0B7DEA3B98D019419C631D36506572113A6EC7CE&thid=OIP.tCTjLEY35uoFRtXD-3M-IQAAAA&mediaurl=https%3A%2F%2Fth.bing.com%2Fth%2Fid%2FR.b424e32c4637e6ea0546d5c3fb733e21%3Frik%3DzsduOhFyZVA2HQ%26riu%3Dhttp%253a%252f%252fimg.ciwong.com%252fi02%252fcgtg%252f5991nfu0rm2oizg0zibszwtuc_16041080.png_260x190.jpg%26ehk%3DVxNFJ0jqJBlpGTHVbwrpoTQrILmbjjiZxn5osTJoYUQ%253d%26risl%3D%26pid%3DImgRaw%26r%3D0&exph=190&expw=260&q=%e4%b8%a4%e4%b8%aa%e7%89%a9%e4%bd%93%e5%af%b9%e6%af%94%e5%9b%be&simid=608004517340533454&form=IRPRST&ck=360ED9A0294CA9306DD0D8C5FE52F8B3&selectedindex=46&ajaxhist=0&ajaxserp=0&vt=0&sim=11 | finegrained_perception (cross-instance) | nan | dev |
|
2,000,693 | What is the object in this picture? | nan | D | Flute | Pipa | Violin | Piano | celebrity_recognition | Internet | finegrained_perception (instance-level) | https://img03.sogoucdn.com/v2/thumb/retype_exclude_gif/ext/auto/crop/xy/ai/w/1109/h/624?appid=200698&url=https://pic.baike.soso.com/ugc/baikepic2/12852/cut-20180110091152-917761434_jpg_1109_739_56506.jpg/0 | dev |
|
3,001,002 | Which is right? | nan | B | One washbasin is on the top of the other | Two washbasins are next to each other | One washbasin is on the bottom of the other | Two washbasins are far from each other | physical_relation | COCO train2014 | relation_reasoning | 6.png | dev |
|
2,000,389 | Why are kangaroos called boxers? | Read the text about kangaroos.
Kangaroos are unusual-looking animals. But their funny-looking bodies help them survive in the wild. Thanks to their strong back legs, kangaroos can jump up to thirty feet high. They also pound their long feet and big tails on the ground to warn other kangaroos of danger.
Kangaroos use their short arms to defend themselves against each other or dangerous animals, such as wild dogs. Some people call kangaroos boxers because of the way they hold their arms when they fight. Kangaroos also sometimes lick their arms on hot days. They do this to cool off. From head to toe, kangaroos use what they have to stay safe and comfortable in the wild. | C | because they lick their arms before fighting | because they have strong back legs | because of how they use their arms to fight | nan | identity_reasoning | scienceqa | attribute_reasoning | nan | dev |
|
2,001,811 | Which of the following captions best describes this image? | nan | A | A person reading a book in a library | A woman applying makeup in front of a mirror | A person taking a photo with a camera | A group of people watching a movie in a theater | image_scene | coarse_perception | nan | dev |
||
2,000,112 | Which one is the correct caption of this image? | nan | A | A soccer player looks up at a soccer ball. | A cat is laying on top of a laptop computer. | A white and red bus is traveling down a road. | There are several pictures of a woman riding a horse at a competition. | action_recognition | description | finegrained_perception (cross-instance) | nan | dev |
|
1,676 | Which Python code can generate the content of the image? | nan | A | print "My name is %s and weight is %d kg!" % ('Zara', 21) | print "My name is %s and weight is %d kg!" % ('Zara', 11) | print "My name is %s and weight is %d g!" % ('Zara', 21) | print "My name is %s and weight is %d kg!" % ('Laura', 21) | structuralized_imagetext_understanding | https://www.runoob.com/python/python-strings.html | logic_reasoning | nan | dev |
|
2,000,699 | Extract text from the image | nan | A | CLOUD CUCKOO LAND | Wonderland | Fantasy World | Imaginary Realm | ocr | TextVQA test-split | finegrained_perception (instance-level) | 1b32c573daac7982.jpg | dev |
|
3,001,389 | What's the profession of the people in this picture? | nan | A | postman | pilot | policeman | mason | identity_reasoning | attribute_reasoning | nan | dev |
||
2,001,214 | What will happen next? | nan | B | the truck is gonna drive straight forward | the truck is gonna turn over | the truck is gonna turn left | both A,B, and C | future_prediction | https://www.youtube.com/watch?v=w6urQm7Prs28 | logic_reasoning | nan | dev |
|
687 | What is the object in this picture? | nan | B | slipper | sneaker | leather shoes | High-heeled shoes | celebrity_recognition | Internet | finegrained_perception (instance-level) | dev |
||
1,302 | what is the color of this object? | nan | A | red | blue | yellow | green | attribute_recognition | finegrained_perception (instance-level) | nan | dev |
||
25 | Which one is the correct caption of this image? | nan | D | 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. | object_localization | description | finegrained_perception (instance-level) | nan | dev |
|
1,000,491 | Which area on the map shows China? | China is the largest country in East Asia. The official name of China is the People's Republic of China. China's eastern coast borders the Pacific Ocean, and its southwestern region borders the Himalayan Mountains. Look at the map. Then answer the question below. | B | A | B | C | D | spatial_relationship | scienceqa | finegrained_perception (cross-instance) | nan | dev |
|
2,001,304 | what is the color of this object? | nan | D | yellow | green | red | blue | attribute_recognition | finegrained_perception (instance-level) | nan | dev |
||
2,001,395 | What's the profession of the people in this picture? | nan | A | waiter | tailor | driver | teacher | identity_reasoning | attribute_reasoning | nan | dev |
||
1,150 | What can be the relationship between the two persons in this image? | nan | B | Father and daughter | Mother and son | Brother and sister | Husband and wife | social_relation | relation_reasoning | nan | dev |
||
2,001,298 | what is the shape of this object? | nan | A | star | Hexagon | oval | heart | attribute_recognition | finegrained_perception (instance-level) | nan | dev |
||
24 | Which one is the correct caption of this image? | nan | D | 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. | object_localization | description | finegrained_perception (instance-level) | nan | dev |
|
1,001,866 | What direction is Turjmenistan in Afhanistan? | nan | A | north | east | south | west | spatial_relationship | https://www.google.com/maps/@44.3563054,26.1089918,4z?entry=ttu | finegrained_perception (cross-instance) | nan | dev |
|
3,001,511 | Which corner doesn't have any food? | nan | C | top-left | bottom-left | bottom-right | top-right | object_localization | finegrained_perception (instance-level) | nan | dev |
||
3,000,646 | Where is the broccoli located in the picture? | nan | B | top left | bottom left | bottom right | top right | object_localization | COCO_test2015 | finegrained_perception (instance-level) | 000000002765.jpg | dev |
|
3,000,529 | What feeling is represented in this image? | nan | B | distressed | happy | sad | engaged | image_emotion | Internet | coarse_perception | nan | dev |
|
1,308 | what is the color of this object? | nan | C | red | blue | yellow | green | attribute_recognition | finegrained_perception (instance-level) | nan | dev |
||
1,001,824 | Which of the following captions best describes this image? | nan | A | A person rock climbing on a mountain | A group of people camping in a forest | A person riding a horse in a field | A woman fishing on a riverbank | image_scene | coarse_perception | nan | dev |
||
2,001,440 | who is this person? | nan | B | Emma Watson | J.K. Rowling | Meghan Markle | Kate Middleton | celebrity_recognition | finegrained_perception (instance-level) | nan | dev |
||
2,000,805 | Which image shows the highest contrast? | nan | D | down left | down right | upper left | upper right | image_quality | koniq10k | coarse_perception | 8844729886_5528731780_2344211137_9346378862_1 | dev |
|
1,001,308 | what is the color of this object? | nan | D | green | red | blue | yellow | attribute_recognition | finegrained_perception (instance-level) | nan | dev |
||
1,403 | What's the profession of the people in this picture? | nan | A | astronaut | chemist | musician | pianist | identity_reasoning | attribute_reasoning | nan | dev |
||
1,001,875 | What direction is Chile in Uruguay? | nan | D | north | east | south | west | spatial_relationship | https://www.google.com/maps/@44.3563054,26.1089918,4z?entry=ttu | finegrained_perception (cross-instance) | nan | dev |
|
3,000,799 | Which image shows the highest sharpness? | nan | A | upper right | down left | down right | upper left | image_quality | koniq10k | coarse_perception | 6609931137_7923574034_6111148526_11407862453_3 | dev |
|
3,001,882 | What direction is Indonesia in Austalia? | nan | C | southwest | southeast | northwest | northeast | spatial_relationship | https://www.google.com/maps/@44.3563054,26.1089918,4z?entry=ttu | finegrained_perception (cross-instance) | nan | dev |
|
1,001,657 | Which Python code can generate the content of the image? | nan | B | list = ["world", "Ok", "Bye!"]
combined_string = " ".join(list)
print(combined_string) | list = ["Hello", "world", "Ok", "Bye!"]
combined_string = " ".join(list)
print(combined_string) | list = ["Hello", "world", "Ok"]
combined_string = " ".join(list)
print(combined_string) | list = ["Hello", "world", "Bye!"]
combined_string = " ".join(list)
print(combined_string) | structuralized_imagetext_understanding | https://zhuanlan.zhihu.com/p/374461056 | logic_reasoning | nan | dev |
|
1,001,792 | Which of the following captions best describes this image? | nan | A | A woman standing on a balcony overlooking a city | A couple sitting on a bench in a park | A group of people walking across a bridge | A person sitting on a rock near a river | image_scene | https://images.unsplash.com/photo-1653316834393-ddaa68981fd6?ixlib=rb-4.0.3&ixid=M3wxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8fA%3D%3D&auto=format&fit=crop&w=1000&q=80 | coarse_perception | nan | dev |
|
1,001,060 | What kind of weather is depicted in the picture? | nan | D | snowy | sunny | rainy | windy | image_scene | coarse_perception | nan | dev |
||
3,001,392 | What's the profession of the people in this picture? | nan | C | postman | singer | tailor | mason | identity_reasoning | attribute_reasoning | nan | dev |
||
1,001,946 | In nature, what's the relationship between these two creatures? | nan | B | Symbiotic relationship | Predatory relationships | Competitive relationships | Parasitic relationships | nature_relation | https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcQAMuEX35GUUtl2uZuphhZNFC0umhfooYDPUvCYs3PLR-uFsk8GDNZFP9a0oomRq3oHYUs&usqp=CAU | relation_reasoning | nan | dev |
|
2,001,898 | What kind of human behavior does this picture describe? | nan | C | An actor is filming a scene on a movie set, reciting lines and taking direction from the director while crew members prepare lighting and sound equipment. | A family is enjoying a day out at an amusement park, riding roller coasters, playing games, and eating cotton candy and popcorn. | A man in a suit with his hands in his pockets stands among a sea of yellow flowers | A man is practicing his skateboard tricks at a skate park, performing flips and grinds with precision and skill. | action_recognition | https://www.zhihu.com/question/36417524 | finegrained_perception (cross-instance) | nan | dev |
|
2,000,334 | What can Hazel and Xavier trade to each get what they want? | Trade happens when people agree to exchange goods and services. People give up something to get something else. Sometimes people barter, or directly exchange one good or service for another.
Hazel and Xavier open their lunch boxes in the school cafeteria. Neither Hazel nor Xavier got everything that they wanted. The table below shows which items they each wanted:
Look at the images of their lunches. Then answer the question below.
Hazel's lunch Xavier's lunch | C | Xavier can trade his broccoli for Hazel's oranges. | Xavier can trade his almonds for Hazel's tomatoes. | Hazel can trade her tomatoes for Xavier's broccoli. | Hazel can trade her tomatoes for Xavier's carrots. | physical_relation | scienceqa | relation_reasoning | nan | dev |
|
3,001,681 | What's the function of the demonstrated object? | nan | D | stir | Water purification | Boiling water | Cut vegetables | function_reasoning | https://www.bing.com/images/search?view=detailV2&ccid=syRfm578&id=1FB2B9C4B244F3017FA1E78FF8A7DF44BEEF4D95&thid=OIP.syRfm578FmkuM7vV0rS-7wHaHa&mediaurl=https%3A%2F%2Fcbu01.alicdn.com%2Fimg%2Fibank%2F2017%2F605%2F072%2F3789270506_1814447136.jpg&exph=750&expw=750&q=%e8%8f%9c%e5%88%80&simid=608003787194595660&form=IRPRST&ck=99036D44A3A0698EDC482F24B14BBF76&selectedindex=5&ajaxhist=0&ajaxserp=0&vt=0&sim=11 | attribute_reasoning | nan | dev |
|
2,000,374 | What type of rock is slate? | This is a piece of slate. Slate usually forms from a sedimentary rock called shale. Slate can form when shale is changed by high temperature and pressure.
Slate is usually dark-colored. The word blackboard comes from the color of slate. Decades ago, blackboards were made of black slate. | B | sedimentary | metamorphic | igneous | nan | attribute_recognition | scienceqa | finegrained_perception (instance-level) | nan | dev |
|
576 | Which action is performed in this image? | nan | C | making sushi | cooking sausages | making tea | barbequing | action_recognition | action/aras | finegrained_perception (cross-instance) | aras_clips/making_tea/eP5_b02cxoo_0.mp4 | dev |
|
1,000,045 | Which one is the correct caption of this image? | nan | C | a cat standing on the edge of a toilet bowl with its front paws inside of the toilet. | 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. | image_scene | description | coarse_perception | nan | dev |
|
1,001,743 | Which operation of fractions is represented by this formula? | nan | A | Devide | Add | Subtract | Multiply | ocr | finegrained_perception (instance-level) | nan | dev |
||
3,001,057 | What kind of weather is depicted in the picture? | nan | A | rainy | windy | snowy | sunny | image_scene | coarse_perception | nan | dev |
||
1,001,916 | What kind of human behavior does this picture describe? | nan | A | A girl dances in thunderstorm weather | A family is boating on a lake, cruising along the water and enjoying the sunshine and fresh air of a perfect day. | A chef is creating a gourmet meal in a restaurant kitchen, chopping, sautéing, and plating while striving for perfection. | An author is writing a novel in a quiet library, typing away at a keyboard and crafting compelling characters and plotlines. | action_recognition | https://www.zhihu.com/question/36417524 | finegrained_perception (cross-instance) | nan | dev |
|
2,001,048 | What type of environment is depicted in the picture? | nan | A | street | forest | home | shopping mall | image_scene | coarse_perception | nan | dev |
||
1,000,565 | Which style is represented in this image? | nan | B | pencil | photography | HDR | comic | image_style | Internet | coarse_perception | nan | dev |
|
3,001,399 | What's the profession of the people in this picture? | nan | A | chemist | janitor | tailor | driver | identity_reasoning | attribute_reasoning | nan | dev |
||
1,001,198 | What will happen next? | nan | B | the bike is gonna go backwards | the bike is gonna get stuck in the mud | the bike is gonna run forward | both A,B, and C | future_prediction | https://www.youtube.com/watch?v=w6urQm7Prs6 | logic_reasoning | nan | dev |
|
2,000,723 | Who is the person in this image? | nan | B | Morgan Freeman | Elon Musk | Xiang Liu | Lionel Messi | celebrity_recognition | Google | finegrained_perception (instance-level) | nan | dev |
|
2,000,144 | Based on the image, what activity can be inferred that the man is engaging in? | nan | B | The man is practicing yoga in a park. | The man is playing a casual game of catch with a frisbee. | The man is playing soccer in a park. | The man is flying a kite in a grass field. | image_topic | reasoning | coarse_perception | nan | dev |
|
1,000,486 | Which term matches the picture? | Read the text.
There are two kinds of energy: kinetic and potential. Kinetic energy is the energy of a moving object. Wind and flowing water both have kinetic energy. Another type of energy is potential energy. There are different types of potential energy. You can think of potential energy as kinds of stored energy. For example, a compressed spring has elastic potential energy. If it doesn't have something holding it down, its energy will be released and it will spring forward. | A | potential energy | kinetic energy | nan | nan | physical_property_reasoning | scienceqa | attribute_reasoning | nan | dev |
|
1,001,871 | What direction is India in Kyrgyzstan? | nan | C | north | east | south | west | spatial_relationship | https://www.google.com/maps/@44.3563054,26.1089918,4z?entry=ttu | finegrained_perception (cross-instance) | nan | dev |
|
3,001,908 | What kind of human behavior does this picture describe? | nan | A | A man wearing a small hat and holding a red handbag greets those around him warmly with a smile | A writer is brainstorming ideas for a novel in a cozy library, scribbling notes on a notepad and pondering the possibilities. | A family is skiing down a snowy slope, gliding over the powder and enjoying the rush of adrenaline as they cut through the mountain air. | A group of artists are painting a mural on a building façade, using bright colors and bold strokes to create a visually striking masterpiece. | action_recognition | https://www.zhihu.com/question/36417524 | finegrained_perception (cross-instance) | nan | dev |
|
2,001,507 | Which corner doesn't have any plates? | nan | B | bottom-left | bottom-right | top-right | top-left | object_localization | finegrained_perception (instance-level) | nan | dev |
||
1,391 | What's the profession of the people in this picture? | nan | D | mason | postman | singer | soldier | identity_reasoning | attribute_reasoning | nan | dev |
||
1,129 | In this picture, are the two butterfly wings the same shape? | nan | B | same | Not the same | Can't judge | nan | attribute_comparison | http://k.sinaimg.cn/n/sinakd10110/113/w576h337/20200813/ff91-ixreehp4093373.jpg/w700d1q75cms.jpg | finegrained_perception (cross-instance) | nan | dev |
|
2,000,597 | What is the color of the large shiny sphere? | nan | A | purple | cyan | red | green | attribute_recognition | Clevr | finegrained_perception (instance-level) | CLEVR_val_000000.png | dev |
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1,000,001 | What is correct Python code to generate the content of the image? | nan | A | fruits = ["apple", "banana", "cherry"]\nfor x in fruits:\n print(x) | 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 | structuralized_imagetext_understanding | code | logic_reasoning | nan | dev |
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294 | Think about the magnetic force between the magnets in each pair. Which of the following statements is true? | The images below show two pairs of magnets. The magnets in different pairs do not affect each other. All the magnets shown are made of the same material. | A | The magnetic force is stronger in Pair 1. | The magnetic force is stronger in Pair 2. | The strength of the magnetic force is the same in both pairs. | nan | physical_property_reasoning | scienceqa | attribute_reasoning | nan | dev |
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1,563 | The object shown in this figure: | nan | D | 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. | physical_property_reasoning | https://bkimg.cdn.bcebos.com/pic/c8177f3e6709c93d70cf69e8cc76efdcd100baa1fed3 | attribute_reasoning | nan | dev |
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1,000,507 | Which can be the associated text with this image posted on twitter | nan | B | If you have time, lets watch the ad together! I think the ad will look good too! Actually there are 2 giant screens , but sad that we dont have fans to help us to take recording in time square @_@ Actually the ad is very nice, I may try to buy him the same LED ad again. | 19 years ago today, may 6, 2004, the last episode of friends was broadcasted live in times square | The Time Square demonstration is a spillover from the nationwide protests in Pakistan sparked by the arrest of former Prime Minister Imran Khan | I’m so happyyyy #Jay_TimesSquare | celebrity_recognition | socialmedia | finegrained_perception (instance-level) | nan | dev |
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761 | Who is the person in this image? | nan | B | Jack Ma | Kanye West | Steve Jobs | Xiang Liu | celebrity_recognition | Google | finegrained_perception (instance-level) | nan | dev |
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3,000,692 | What is the name of this photograph? | nan | D | Starry Night | Sunflowers | Self-Portrait with Bandaged Ear | Mona Lisa | celebrity_recognition | Internet | finegrained_perception (instance-level) | dev |
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1,452 | who is this person? | nan | D | Hailee Steinfeld | Sridevi | Sandra Oh | Deepika Padukone | celebrity_recognition | finegrained_perception (instance-level) | nan | dev |
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1,314 | what is the color of this object? | nan | A | purple | pink | gray | orange | attribute_recognition | finegrained_perception (instance-level) | nan | dev |
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1,000,448 | Which term matches the picture? | Read the text.
Butterflies and moths are easily mistaken for each other, but one distinction between them often appears during their pupal stage. When most butterfly caterpillars reach full size, they attach themselves to a leaf or other object and shed their skin a final time, forming a chrysalis, a hard, shell-like skin, which protects the pupa inside. The chrysalis may be dull and rough or shiny and smooth, usually blending into its surroundings. Most moth caterpillars, by contrast, create a cocoon to protect the pupa, rather than forming a chrysalis. The cocoons usually resemble hard silk pouches, but some moths also incorporate materials like hairs and twigs. | A | chrysalis | cocoon | nan | nan | object_localization | scienceqa | finegrained_perception (instance-level) | nan | dev |
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1,000,445 | According to the text, what evidence of a volcanic eruption did the captain observe? | Before sunrise on November 14, 1963, the crew of the fishing boat Isleifur II had just finished putting their lines in the ocean off the southern coast of Iceland. As the crew waited to have breakfast, a strong smell of sulfur drifted over the boat. At first, crew members thought that the cook had burned the eggs or that something was wrong with the boat's engine. But when the sun started to rise, the crew saw black smoke billowing from the water a few kilometers away.
The captain of the Isleifur II assumed the smoke was coming from a boat that was on fire, so he sailed closer to try to help. As the Isleifur II approached the smoke, the surface of the sea grew rough. The captain and crew saw flashes of lightning in the column of smoke and glowing pieces of molten rock shooting up out of the water. The captain realized this was not a burning boat. It was a volcano erupting under the water!
Figure: the erupting undersea volcano seen by the sailors on the Isleifur II. | C | He knew his crew had finished putting their fishing lines in the ocean. | He heard a report on the radio warning about a volcanic eruption. | He smelled sulfur and then realized it was not coming from his boat. | nan | future_prediction | scienceqa | logic_reasoning | nan | dev |
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2,000,118 | Which one is the correct caption of this image? | nan | A | Three men all eating sub sandwiches at a restaurant. | a cat that is drinking out of a sink | You will not get anywhere if you open these doors and try to pass through. | A corner bathtub in a very clean bathroom. | action_recognition | description | finegrained_perception (cross-instance) | nan | dev |
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1,000,947 | What's the function of the demonstrated object? | nan | A | control the cursor on a computer screen and input text | supply water | used as decorations | touchscreens instead of a physical keyboard | function_reasoning | COCO train2014 | attribute_reasoning | 20.png | dev |
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2,001,497 | Which corner doesn't have any fruits? | nan | C | bottom-left | bottom-right | top-right | top-left | object_localization | finegrained_perception (instance-level) | nan | dev |
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1,816 | Which of the following captions best describes this image? | nan | D | A person swimming in a pool | A group of people sunbathing on a beach | A person skiing down a mountain | A woman doing yoga in a park | image_scene | coarse_perception | nan | dev |
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1,000,048 | Which one is the correct caption of this image? | nan | B | Three boys posing with their helmets on and their bikes. | 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 | image_scene | description | coarse_perception | nan | dev |
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1,001,399 | What's the profession of the people in this picture? | nan | C | tailor | driver | chemist | janitor | identity_reasoning | attribute_reasoning | nan | dev |