[{"object": "aerosol_can", "object_id": 1, "gpt3_output": "\n\n{\"type\": \"vapour\", \"description\": \"white, with a light blue top\", \"similar objects\": [\"soda can\", \"gas can\", \"gas station\", \"cigarette\"]}"}, {"object": "air_conditioner", "object_id": 2, "gpt3_output": "\n\nThe model should focus on those objects that have a type of \"object\" in the input, with that type being listed under the \"type\" field. For this example, the model would focus on the zucchini and the ambulance."}, {"object": "airplane", "object_id": 3, "gpt3_output": "\n\n{\"type\": \"aircraft\", \"description\": \"black, white, and red; has a wingspan; can fly\", \"similar objects\": [\"bomber\", \"pilots\", \"pilots\"]"}, {"object": "alarm_clock", "object_id": 4, "gpt3_output": "\n\n{\"type\": \"telecommunications\", \"description\": \"round, has a beep sound\", \"similar objects\": [\"beacon\", \"siren\"]"}, {"object": "alcohol", "object_id": 5, "gpt3_output": "\n\n{\"type\": \"alcohol\", \"description\": \"white, has a gootrope at the end\", \"similar objects\": [\"soda\", \"wine\", \"screwdriver\"]}"}, {"object": "alligator", "object_id": 6, "gpt3_output": "\n\n{\"type\": \"fish\", \"description\": \"black, white, and green; has a long tail\", \"similar objects\": [\"gill\", \"chub\", \"gilliam\"]"}, {"object": "almond", "object_id": 7, "gpt3_output": "\n\n{\"type\": \"almond\", \"description\": \"almond; has a sweet flavor\", \"similar objects\": [\"almond milk\", \"almond bowl\", \"almond milk can\"]}"}, {"object": "ambulance", "object_id": 8, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"red; has a glaring siren; could with a stretcher\", \"similar objects\": [\"police car\", \"taxi\", \"garbage truck\"]}"}, {"object": "amplifier", "object_id": 9, "gpt3_output": "\n\nThe object detection model should focus on finding objects with similar characteristics that are affected by the same force and volume. The model should also be able todetermine that these objects are affected by the same disease and are related to the same problem."}, {"object": "anklet", "object_id": 10, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"small; has a strap\", \"similar objects\": [\" anklet \", \"bangle \", \" anklet \"],"}, {"object": "antenna", "object_id": 11, "gpt3_output": "\n\nThe input should focus on features that are common to all objects, such as smooth, cylindrical objects with green or brown stems, and objects that have a green or brown stem but are not round or smooth."}, {"object": "apple", "object_id": 12, "gpt3_output": "\n\nThe objects in the input could be objects that are all objects, such as a zucchini and a tomato. Alternatively, the input could be a health supplement, like a apple."}, {"object": "applesauce", "object_id": 13, "gpt3_output": "\n\n{\"type\": \"servings\", \"name\": \"savedss\", \"data\": \"\n\nThe objects in the input can be either objects (vegetables, animals, etc.), or names (zebra, apple, banana, pear). The models that should focus on for an input with that type of content are those that are responsible for creating and maintaining names for input names."}, {"object": "apricot", "object_id": 14, "gpt3_output": "\n\n{\"type\": \"image\", \"description\": \"A apricot.png\", \"size\": \"\n\nA apricot.png"}, {"object": "apron", "object_id": 15, "gpt3_output": "\n\n{\"type\": \"appearance\", \"description\": \"round, smooth, has a handle\", \"similar objects\": [\"coaster\", \"trucker's bus\", \"tourist information card\"]}"}, {"object": "aquarium", "object_id": 16, "gpt3_output": "\n\n{\"type\": \"aquarium\", \"description\": \"black and white, with a clear top\", \"similar objects\": [\"giraffe\", \" dolphin \", \" \n\" tank \"}\""}, {"object": "arctic_(type_of_shoe)", "object_id": 17, "gpt3_output": "\n\n{\"type\": \"footwear\", \"description\": \"crystals and balls; ice and snow; winter\"; \"similar objects\": [\"snowboard\", \"shoe\", \"bunny\", \"cat\"]}"}, {"object": "armband", "object_id": 18, "gpt3_output": "\n\nThe features that should be focus for an object detection model that smells zucchini should be the cylindrical shape, the smooth texture, and the green color. The model should be able to identify zucchini as a food item, but should not be able to identify the object itself."}, {"object": "armchair", "object_id": 19, "gpt3_output": "\n\n{\"type\": \"toy\", \"description\": \"round, has a handle\", \"similar objects\": [\"arm\", \"chair\", \"toy\"]"}, {"object": "armoire", "object_id": 20, "gpt3_output": "\n\n{\"type\": \"item\", \"description\": \"red; has a handle; could have a lid\", \"similar objects\": [\"mirror\", \"coaster\", \"trucker's bus\"]}"}, {"object": "armor", "object_id": 21, "gpt3_output": "\n\n{\"type\": \"armour\", \"description\": \"black, with a red stripe running down the middle\", \"similar objects\": [\"pantaloons\", \"turban\", \"eyebrows\", \"hat\"]}"}, {"object": "artichoke", "object_id": 22, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for artichokes is their similarity objects. This means that the model should look for things that are like artichokes, such as having their shape, size, and color."}, {"object": "trash_can", "object_id": 23, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "ashtray", "object_id": 24, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"ashtray\", \"description\": \"\n\nThe features of an object detection model that focuses on are needed for objects that are cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves."}, {"object": "asparagus", "object_id": 25, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"asparagus\", \"zucchini\", \"gazelle\"]}"}, {"object": "atomizer", "object_id": 26, "gpt3_output": "\n\nThe features that should be focus for an object detection model that smells like an atomizer are making it round and having its top be clear, as well as making the body flat and have its sides made of material that is non-metallic."}, {"object": "avocado", "object_id": 27, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, smooth; has a green skin and green seeds\", \"similar objects\": [\"grape\", \"butterfly\", \"chicken\"]}"}, {"object": "award", "object_id": 28, "gpt3_output": "\n\n{\"type\": \"gift\", \"name\": \"Gift of the award\", \"value\": \"\", \"similar objects\": [\"gift card\", \"gift box\"]}"}, {"object": "awning", "object_id": 29, "gpt3_output": "\n\nThe features that should be focus for an object detection model that smells like an apple would be the shape of the apple, the size of the apple, and the color of the apple."}, {"object": "ax", "object_id": 30, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for objects is the object's type. For example, an object that is looking for objects would include vegetables. The type of an object would focus on its type, such as a vegetable for object detection models that are looking for objects, the handle for example."}, {"object": "baboon", "object_id": 31, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"light brown, black, smooth; could have a scaly surface\", \"similar objects\": [\"baboon\", \"cat\", \"otter\"]}"}, {"object": "baby_buggy", "object_id": 32, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"red; has a gear wheel\", \"similar objects\": [\"car seat\", \"wading pool\", \"infant pool\"]}"}, {"object": "basketball_backboard", "object_id": 33, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"backboard\", \"description\": \"a small, round, metal board with a clear plastic cover\", \"similar objects\": [\"sportscar\", \"pump\", \"pumpa\"]"}, {"object": "backpack", "object_id": 34, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves \"\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "handbag", "object_id": 35, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"handbag\", \"description\": \"\"}"}, {"object": "suitcase", "object_id": 36, "gpt3_output": "\n\n{\"type\": \"item\", \"description\": \"red, with a handle\", \"similar objects\": [\"key\", \"wallet\", \"wallet case\"]}"}, {"object": "bagel", "object_id": 37, "gpt3_output": "\n\n{\"type\": \"cake\", \"description\": \"white, with a hole in the top\", \"similar objects\": [\"chocolate\", \"flour\", \"flourish\"]"}, {"object": "bagpipe", "object_id": 38, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for evidence of life is its history of playing bagpipe. The bagpipe is a popular music instrument that is played with a wand or stick. The model should also be good at playing the bagpipe, as well as other bagpipes, steel drums, and other bagpipe instruments."}, {"object": "baguet", "object_id": 39, "gpt3_output": "\n\n{\"type\": \"sunglasses\", \"description\": \"light blue, smooth, has a lens that can be opened\", \"similar objects\": [\"sunglasses\", \"sunglasses case\"]}"}, {"object": "bait", "object_id": 40, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, red, green, blue\", \"similar objects\": [\"gazelle\", \"rhinoceros\", \" elephant \", \"island\", \"cat\"]}"}, {"object": "ball", "object_id": 41, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "ballet_skirt", "object_id": 42, "gpt3_output": "\n\n{\"type\": \"item\", \"description\": \"pink, with a blue and green striping\", \"similar objects\": [\"strawberry\", \"chocolate cake\", \"apple\"]}"}, {"object": "balloon", "object_id": 43, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "bamboo", "object_id": 44, "gpt3_output": "\n\n{\"type\": \"trees\", \"description\": \"round, green, has a stem; can be chopped into small pieces\", \"similar objects\": [\"maple\", \"honeydew\", \"grape\"]}"}, {"object": "banana", "object_id": 45, "gpt3_output": "\n\n{\"type\": \"noun\", \"description\": \"a fruit\", \"usage\": \"noun\"}\n\nInput:\n\n{\"type\": \"object\", \"description\": \"a vegetable\", \"usage\": \"noun\"}"}, {"object": "Band_Aid", "object_id": 46, "gpt3_output": "\n\nThe Band Aid model should focus on cylindrical objects with smooth stems, while the apple and banana models should focus on round objects with rough stems."}, {"object": "bandage", "object_id": 47, "gpt3_output": "\n\n{\"type\": \"text\", \"message\": \"blood\", \"type\": \"text\"}, {\"type\": \"text\", \"message\": \"blood\", \"type\": \"text\"},"}, {"object": "bandanna", "object_id": 48, "gpt3_output": "\n\n{\"type\": \"namestring\", \"name\": \"namestring\", \"email\": \"virginia@email.com\", \"has\": \"string\", \"description\": \"A bandanna is a piece of cloth with a name or address on it. It is used to keep track of notes or letters in a text editor.\""}, {"object": "banjo", "object_id": 49, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, with a white spot in the middle of the head\", \"similar objects\": [\"banana\", \"giraffe\", \"monkey\"]}"}, {"object": "banner", "object_id": 50, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"banana\", \"description\": \"\n\nThe zucchini and the apple both have a smooth surface and are of different sizes. The zebra has rough stems and could be sliced into round pieces. The banner has green leaves to give it an effect of smooth surface."}, {"object": "barbell", "object_id": 51, "gpt3_output": "\n\n{\"type\": \"barbell\", \"description\": \"black, with a sharp point\", \"similar objects\": [\"soup can\", \"fry pan\"]}"}, {"object": "barge", "object_id": 52, "gpt3_output": "\n\n{\"type\": \"boat\", \"description\": \"black, with a white/black hull\", \"similar objects\": [\"coaster\", \"ship\", \"coaster ride\"]}"}, {"object": "barrel", "object_id": 53, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"round, has a handle\", \"similar objects\": [\"barrel\", \"socket\", \"converter\", \"octopus\"]}"}, {"object": "barrette", "object_id": 54, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"red; has a small hole in the center\", \"similar objects\": [\"bead\", \"bunny\", \"flowers\"]}"}, {"object": "barrow", "object_id": 55, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves \"\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "baseball_base", "object_id": 56, "gpt3_output": "\n\nThe objects in the input should be objects that are similar to each other. For example, the object \"type\" should focus on objects that are \"type\" objects. The objects \"description\" and \"similar objects\" should focus on objects that are objects that are similar to the object \"description.\""}, {"object": "baseball", "object_id": 57, "gpt3_output": "\n\nThe input should be a specific object, such as a zucchini. The output should be a list of objects that are similar to zucchini."}, {"object": "baseball_bat", "object_id": 58, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for baseball bats is the model's ability to identify objects that have baseball bats as a target.\n\nInput: fire hydrant, Output:\n\nThe feature that should focus on for an object detection model that is looking for fire hydrants is their ability to identify their target as being a fire hydrant."}, {"object": "baseball_cap", "object_id": 59, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"round, has a brimmed hat\", \"similar objects\": [\"hat\", \"sunglasses\", \"sunglasses case\"]}"}, {"object": "baseball_glove", "object_id": 60, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "basket", "object_id": 61, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"Bread\", \"description\": \"round, smooth, has a top\", \"similar objects\": [\"bread\", \"bag\", \"bag of grapes\"]}"}, {"object": "basketball", "object_id": 62, "gpt3_output": "\n\n{\"type\": \"ball\", \"description\": \"light blue\", \"similar objects\": [\"ballpoint pen\", \"dip pen\"]}"}, {"object": "bass_horn", "object_id": 63, "gpt3_output": "\n\nThe focus of an object detection model's work should be on specific objects that are commonly used in an input of this type. These objects are called \"type objects.\" They are specific objects that are used in this input, and they have specific features that make them used that way. The focus of an object detection model's work should be on those type objects."}, {"object": "bat_(animal)", "object_id": 64, "gpt3_output": "\n\nThe bat (animal) feature should focus on the bat's body and wings, and its behavior should be described. The bat's wings could be dark, and its body could be smooth."}, {"object": "bath_mat", "object_id": 65, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"Wok\", \"description\": \"round, deep, has a handle\", \"similar objects\": [\"pan\", \"pot\", \"frying pan\"]}"}, {"object": "bath_towel", "object_id": 66, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"Bath towel\", \"material\", \"tool\", \"function\"}, \"type\", \"description\"}, \"color\"}, \"flavor\"}, \"ingredient\"}, \"use\"}\n\nThe following objects are all objects that can be identified by their features:\n\nInput: zucchini, Output: {\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]"}, {"object": "bathrobe", "object_id": 67, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"Bathrobe\", \"type_name\": \"Object\"},\n\n {\"type\": \"object\", \"name\": \"Bathrobe\", \"type_name\": \"Object\"},"}, {"object": "bathtub", "object_id": 68, "gpt3_output": "\n\n{\"type\": \"bathroom\", \"description\": \"black and white, has a drain\", \"similar objects\": [\"bath\", \"toilet\", \" sink\"]}"}, {"object": "batter_(food)", "object_id": 69, "gpt3_output": "\n\n{\"type\": \"ingredient\", \"description\": \"dried batter; needs to be mixed with water\", \"similar objects\": [\"batter\", \"dough\", \"doughnut\", \"souvenir\"]}"}, {"object": "battery", "object_id": 70, "gpt3_output": "\n\n{\"type\": \"battery\", \"description\": \"green; has a long life\", \"similar objects\": [\"solar panel\", \"ellipet\", \"cellular phone\"]"}, {"object": "beachball", "object_id": 71, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for zucchini is its type. This model should be able to find zucchini that is of the type \"vegetable\". Additionally, the model should be able to find zucchini that iscyndrical, has a smooth surface, and is sliced into round pieces. The model should also be able to find zucchini that has green leaves."}, {"object": "bead", "object_id": 72, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"Beads\", \"description\": \"Rings, Earrings, Necklaces, Earrings inGold, Silver,Platinum, palladium\" }"}, {"object": "bean_curd", "object_id": 73, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"a type of cheese made from a curd of casein and milk\", \"similar objects\": [\"butter\", \"gravy\", \"gouda\"]}"}, {"object": "beanbag", "object_id": 74, "gpt3_output": "\n\n{\"type\": \"beach ball\", \"description\": \"black, white, smooth\", \"similar objects\": [\"soup can\", \"balloon\", \"fishing net\"]}"}, {"object": "beanie", "object_id": 75, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"small; has a hole in the center\", \"similar objects\": [\" beanie \"],"}, {"object": "bear", "object_id": 76, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, or green; could have a furrowed fur; could be could be tumbling in water\", \"similar objects\": [\"puma\", \"otter\", \"island\"]}"}, {"object": "bed", "object_id": 77, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves \"\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "bedpan", "object_id": 78, "gpt3_output": "\n\n{\"type\": \"utility\", \"description\": \"round, deep, has a handle\", \"similar objects\": [\"pantry\", \"fridge\", \"freeze\", \"uke\"]"}, {"object": "bedspread", "object_id": 79, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"bedspread\"},\n\n{\"type\": \"object\", \"name\": \"bed\", {\"type\": \"vegetable\"},\n\n{\"type\": \"object\", \"name\": \"bedspread\"},"}, {"object": "cow", "object_id": 80, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black and white stripes; has a long mane\", \"similar objects\": [\"giraffe\", \"elephant\", \"horse\"]}"}, {"object": "beef_(food)", "object_id": 81, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"beef\", \"chicken\", \"chicken salad\"]}"}, {"object": "beeper", "object_id": 82, "gpt3_output": "\n\nThe ability to identify objects by their sounds."}, {"object": "beer_bottle", "object_id": 83, "gpt3_output": "\n\n{\"type\": \"bottle\", \"name\": \"Cigarette\", \"style\": \"bottle\", \"similar objects\": [\"packet of cigarettes\", \"packet of cigars\"]}"}, {"object": "beer_can", "object_id": 84, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cyan, has a smooth surface\", \"similar objects\": [\"banana\", \"grocery store\", \"coaster\"]"}, {"object": "beetle", "object_id": 85, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for Vegetables is whether or not the object is cylindrical, with a smooth surface. The object should also be able to have different colors, different descriptions, and have similar objects as other objects."}, {"object": "bell", "object_id": 86, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for evidence of life is its size. An object's size should be able to be determined based on its dimensions, such as its diameter or length. Additionally, an object's shape should be known, such as the way it turns when picked up. Other features that may be looked for include its color, texture, or size."}, {"object": "bell_pepper", "object_id": 87, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for food is its size. Other features that might be important for an object detection model to focus on include its shape, color, and size."}, {"object": "belt", "object_id": 88, "gpt3_output": "\n\n{\"type\": \" belt \", \"description\": \"black, with a red band\", \"similar objects\": [\"sling\", \" belt \"\", \" belt \"\", \" belt \"\", \" belt \"\", \" belt \"\", \" belt \"\", \" belt \"\", \" belt \"\", \" belt \"\", \" black \"\", \" red \"\", \" green \"\", \" blue \"\", \" orange \"\", \" vanilla \"\", \"ittee\"]}"}, {"object": "belt_buckle", "object_id": 89, "gpt3_output": "\n\n{\"type\": \"beloved\", \"image\", \"preference\": \"image\", \"similar objects\": [\"coaster\", \"bucket\"]}"}, {"object": "bench", "object_id": 90, "gpt3_output": "\n\n{\"type\": \"bed\", \"description\": \"black, with a red upholstery\", \"similar objects\": [\"cage\", \"bench\", \"towel\"]"}, {"object": "beret", "object_id": 91, "gpt3_output": "\n\nThere are many different types of object detection models that could be used for an input of zucchini, apple, ambulance, beret, and lantern. The focus could be on those models that have smooth surfaces, cylindrical shapes, and green or similar colors."}, {"object": "bib", "object_id": 92, "gpt3_output": "\n\n{\"type\": \"textbook\", \"id\": \"102059\", \"location\": \"102059\", \"published\": \"2010-12-15\", \"title\": \"The Art of Cookery\", \"published_by\": \"www.eatwell.org\", \"type\": \"book\", \"sizes\": \"large\", \"price\": \"www.eatwell.org\", \"weight\": \"www.eatwell.org\", \"a4qids\": \"102059\"}\n\nThe Art of Cookery by\n\nwww.eatwell.org\n\nThe Art of Cookery is"}, {"object": "Bible", "object_id": 93, "gpt3_output": "\n\nThe input should be a list of objects that all have a similar shape and color. For example, the zucchini should have a round shape, the apple should have a brown shape, and the ambulance should have smooth sides and a stretcher for a vehicle."}, {"object": "bicycle", "object_id": 94, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for evidence of life is its ability to identify similar objects. Object detection models that are looking for evidence of damage or illness will likely focus on objects with similar features and patterns."}, {"object": "visor", "object_id": 95, "gpt3_output": "\n\n{\"type\": \"face\", \"description\": \"opaque; small eyes; has a long snout\", \"similar objects\": [\"seaweed\", \"sunglasses\", \"sunglasses case\"]}"}, {"object": "billboard", "object_id": 96, "gpt3_output": "\n\n{\"type\": \"image\", \"uuid\": \"cwc4d8b2-fcd4-11e8-8aon-v9jd-v9jd-v9jd-v9jd-v9jd-v9jd-v9jd-v9jd-v9jd-v9jd-v9jd-v9jd-v9jd-v9jd-v9jd-v9jd-v9jd-v9jd-v9jd"}, {"object": "binder", "object_id": 97, "gpt3_output": "\n\n{\"type\": \"book\", \"description\": \"round, has a cover\", \"similar objects\": [\"patent book\", \"patent office\", \"recliner\", \"bed\", \"trucker\", \"container\", \"trucker truck\"]"}, {"object": "binoculars", "object_id": 98, "gpt3_output": "\n\n{\"type\": \"object\", \"description\": \"black, with a red band around the pupil\", \"similar objects\": [\"umbrella\", \"scope\", \" binoculars\"]"}, {"object": "bird", "object_id": 99, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, or green; could have a beak\", \"similar objects\": [\"parrot\", \"clam\", \"gazelle\"]}"}, {"object": "birdfeeder", "object_id": 100, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \"vegetable\", \"similar objects\": [\"fruit\", \"vegetable\", \"carrot\"]}"}, {"object": "birdbath", "object_id": 101, "gpt3_output": "\n\n{\"type\": \"aquarium\", \"water level\", \"status\": \" Absent\", \"similar objects\": [\"giraffe\", \"monkey\"]}"}, {"object": "birdcage", "object_id": 102, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"Zucchini\", \"description\": \"The zucchini is a vegetable that can be found in the grocery store. It is smooth and has a green skin. The zucchini can be sliced into round pieces and has green leaves. The leaves could be sliced into brown pieces. The zucchini is a food that is high in nutrients and is a good source of dietary fiber. The zucchini is a good source of protein and has a lot of nutrients. The zucchini is a good source of nutrients and is a good source of protein.\""}, {"object": "birdhouse", "object_id": 103, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "birthday_cake", "object_id": 104, "gpt3_output": "\n\nThe object detection model should focus on objects that have the same type as the object it is trying to detect. For example, a zucchini would be a vegetable, while a birthday cake would be a cake, regardless of type."}, {"object": "birthday_card", "object_id": 105, "gpt3_output": "\n\n{\"type\": \"card\", \"description\": \"\", \"similar objects\": [\"card\", \"cake\", \"cat\"]}"}, {"object": "pirate_flag", "object_id": 106, "gpt3_output": "\n\nThe ambulance should focus on the round vehicle with the siren."}, {"object": "black_sheep", "object_id": 107, "gpt3_output": "\n\n{\"type\": \" animal \", \"description\": \"black and white stripes; has a long mane\", \"similar objects\": [\" horse \", \"giraffe \", \"elephant \"],"}, {"object": "blackberry", "object_id": 108, "gpt3_output": "\n\n{\"type\": \"apple\", \"description\": \"reddish brown, has a smooth surface\", \"similar objects\": [\"appleseed\", \"grape\", \"grape\",\", \"grape\", \"grape\", \"grape\", \"grape\", \"grape\", \"grape\", \"grape\", \"grape\", \"grape\", \"grape\", \"grape\", \"grape\", \"grape\", \"grape\", \"grape\", \"grape\", \"grape\", \"grape\", \"grape\", \"grape\", \"grape\", \"grape\", \""}, {"object": "blackboard", "object_id": 109, "gpt3_output": "\n\n{\"type\": \"board\", \"description\": \"round, has a thin surface\", \"similar objects\": [\"board\", \"couch\", \"towel\"]"}, {"object": "blanket", "object_id": 110, "gpt3_output": "\n\n{\"type\": \" blankets \", \"description\": \"soft, thin, has a deep downwind corner\", \"similar objects\": [\"pilling\", \"douche\", \"cotton\"]}"}, {"object": "blazer", "object_id": 111, "gpt3_output": "\n\n{\"type\": \"clothing\", \"description\": \"black, white, red; could have a deep V-shaped crease in the fabric\", \"similar objects\": [\"cardigan\", \"shirt\", \"coat\"]}"}, {"object": "blender", "object_id": 112, "gpt3_output": "\n\n{\"type\": \"blender\", \"description\": \"a tool that smooths out the surface of a drink\", \"similar objects\": [\"onion\", \"chopstick\", \"servevy\"]}"}, {"object": "blimp", "object_id": 113, "gpt3_output": "\n\n{\"type\": \"image\", \"description\": \"\", \"url\": \"http://www.gizmond.com/wp-content/uploads/2013/07/zucchini-image.jpg\", \"alt\": \"Zucchini Image\""}, {"object": "blinker", "object_id": 114, "gpt3_output": "\n\nThe model should focus on objects that have a specific properties, such as cylindrical, smooth, green, or rough stems. The model should also be able to create round pieces and green leaves."}, {"object": "blouse", "object_id": 115, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"Blouse\", \"description\": \"A blouse is a shirt that is made of fabric, usually blue, that is worn over the back of it. The shirt is made of front and back necklines and has a collar and sleeves. The front and back necklines are usually different colors. The sleeves are usually short and wide.\"}"}, {"object": "blueberry", "object_id": 116, "gpt3_output": "\n\n{\"type\": \"fruit\", \"description\": \"red, round, has a stem\", \"similar objects\": [\"apple\", \"banana\", \"pear\"]}"}, {"object": "gameboard", "object_id": 117, "gpt3_output": "\n\n{\"type\": \"game\", \"name\": \"\", \"description\": \"\"}"}, {"object": "boat", "object_id": 118, "gpt3_output": "\n\n{\"type\": \"boat\", \"description\": \"black, with a white superstructure\", \"similar objects\": [\"coaster\", \"raft\", \"island\"]}"}, {"object": "bob", "object_id": 119, "gpt3_output": "\n\nThe features that should be focus for an object detection model that smells like Bob are turning it into a model of Bob, producing a model of Bob from scratch, and learning how to make models of Bob from models of Bob."}, {"object": "bobbin", "object_id": 120, "gpt3_output": "\n\nThe features that should be focus for an object detection model that smells zucchini should be the cylindrical shape, the smooth surface, and the green color. The model should be able to identify zucchini as a vegetable, the description should be accurate, and the model should be able to identify the ingredients of zucchini as well as the object's siblings."}, {"object": "bobby_pin", "object_id": 121, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"bobby pin\", \"description\": \"a small, round, black object\", \"similar objects\": [\"ballpoint pen\", \"pencil\", \"inking stock\"]}"}, {"object": "boiled_egg", "object_id": 122, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that finds eggs is the type of egg. Other features that could be included in an object detection model include the description, size, color, and potential for development."}, {"object": "bolo_tie", "object_id": 123, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"red; has a hanger for it to hang from\", \"similar objects\": [\"bunny\", \"honeycomb\", \"turban\"]}"}, {"object": "deadbolt", "object_id": 124, "gpt3_output": "\n\n{\"type\": \"lock\", \"description\": \"round, has a keyhole\", \"similar objects\": [\"keyboard\", \"lock\"]"}, {"object": "bolt", "object_id": 125, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"small, black, has a hole in the head\", \"similar objects\": [\"keyboard\", \"tape measure\", \"tape\"], \"internal\":[]"}, {"object": "bonnet", "object_id": 126, "gpt3_output": "\n\nThe features that should be focus for an object detection model that smells like an apple would be the shape of the apple, the size of the apple, and the color of the apple."}, {"object": "book", "object_id": 127, "gpt3_output": "\n\n{\"type\": \"book\", \"description\": \"The Catcher in the Rye\", \"similar objects\": [\"horses\", \"bat\", \"batchelor\"]}"}, {"object": "bookcase", "object_id": 128, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"bookcase\", \"description\": \"round, with a lid\", \"similar objects\": [\"coaster\", \"dungeon\", \"castle\"]}"}, {"object": "booklet", "object_id": 129, "gpt3_output": "\n\nThe objects in the input could be objects that are all objects, such as zucchini and apple, or you could focus on specific types of objects, such as ambulance and vehicle."}, {"object": "bookmark", "object_id": 130, "gpt3_output": "\n\n{\"type\": \"bookmark\", \"href\": \"https://www.britannica.com/biography/John-G-F-C-K-M-O-S-R-T-U-V-W-X-Y-Z-A-B-C-D-E-G-F-H-I-J-K-L-M-N-O-P-Q-R-S-T-U-V-W-X-Y-Z-A-C-D-E-G-F-H-I-J"}, {"object": "boom_microphone", "object_id": 131, "gpt3_output": "\n\nThe feature that should focus on for an input with a lot of content is the model's ability to detect objects. For objects, object detection models should be able to detect:\n\n-Cylindrical objects: This includes things like woks, cookers, and ambulances.\n\n-Objects that have a smooth surface: These include vegetables, fruits, and animals.\n\n-Objects that are round or have rough stems: These include zucchini, animals, and vegetables.\n\n-Objects that are sliced into round pieces: This includes the ambulance, boom microphone, and lantern."}, {"object": "boot", "object_id": 132, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"type_name\": \"vegetable\"},\n\n{\"type\": \"object\", \"name\": \"crab\", \"type_name\": \"crusty_crab\"},\n\n{\"type\": \"object\", \"name\": \"apple\", \"type_name\": \"fruit\"},\n\n{\"type\": \"object\", \"name\": \"giraffe\", \"type_name\": \"elephant\"},\n\n}"}, {"object": "bottle", "object_id": 133, "gpt3_output": "\n\n{\"type\": \"vitamin\", \"description\": \"a type of water droplet; contains a water droplet of a vitamin\", \"similar objects\": [\"drink\", \"bottle\", \"tea pot\"]}"}, {"object": "bottle_opener", "object_id": 134, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for bottles is the model's ability to identify bottles as being from the right side of the stove. \n\nInput: fire hydrant, Output: \n\nThe feature that should focus on for an object detection model that is looking for fire hydrants is their ability to identify them as being from the right side of the stove."}, {"object": "bouquet", "object_id": 135, "gpt3_output": "\n\n{\"type\": \"flower\", \"description\": \"red, with a white band around the center\", \"similar objects\": [\"honeydew\", \"snowdrop\", \"lily top\", \"violet top\"]}"}, {"object": "bow_(weapon)", "object_id": 136, "gpt3_output": "\n\n{\"type\": \"bow\", \"name\": \"arrow\", \"properties\": [\"vibration\", \"durability\", \"x\", \"y\", \"z\"]}"}, {"object": "bow_(decorative_ribbons)", "object_id": 137, "gpt3_output": "\n\n{\"type\": \"bow\", \"id\": \"10\", \"name\": \"Bows\", \"description\": \"\n\nBows are used to guide an user in bow-related tasks, such as making arrows or arrows with bows. Bowstrings and bowstrings with arrows are also bow features."}, {"object": "bow-tie", "object_id": 138, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"red; has a tie-dance with you\", \"similar objects\": [\"fishing net\", \"fishing rod\", \"fishing spear\"]}"}, {"object": "bowl", "object_id": 139, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "pipe_bowl", "object_id": 140, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"name\": \"vegetable\", \"description\": \"cylindrical, smooth; could have rough stems; could be sliced into round pieces; could has green leaves\"}"}, {"object": "bowler_hat", "object_id": 141, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"small; has a bow at the back\", \"similar objects\": [\"bow\", \"hat\", \"ballpoint pen\"]}"}, {"object": "bowling_ball", "object_id": 142, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"small; has a handle and a ball\", \"similar objects\": [\"ball\", \"ballpoint pen\", \"ballpoint pen and pen\"]"}, {"object": "box", "object_id": 143, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves \"\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "boxing_glove", "object_id": 144, "gpt3_output": "\n\n{\"type\": \" Goods \", \"description\": \"A glove with a ring around the inside of the hand\", \"similar objects\": [\"boxing gloves\", \"boxing fighter\", \"boxing movie\", \"boxing match\", \"boxing match in progress \", \"boxing gloves\", \"boxing match prediction\"]}"}, {"object": "suspenders", "object_id": 145, "gpt3_output": "\n\n{\"type\": \"clothes\", \"description\": \"black, white, red, green, blue\", \"similar objects\": [\"pants\", \"shoes\", \"sunglasses\"]}"}, {"object": "bracelet", "object_id": 146, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"small; has a strap\", \"similar objects\": [\"bracelet\", \"watch\"]"}, {"object": "brass_plaque", "object_id": 147, "gpt3_output": "\n\nThe plaque should have a smooth surface with some bumps and crevices. The plaque should also be of a high-quality, durable material that can be used for a long time."}, {"object": "brassiere", "object_id": 148, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"small; has a handle\", \"similar objects\": [\"bra\", \"braiding tool\"]}"}, {"object": "bread-bin", "object_id": 149, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves \"\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "bread", "object_id": 150, "gpt3_output": "\n\n{\"type\": \"ingredient\", \"description\": \"bread dough\", \"similar objects\": [\"butter\", \"flour\", \"flour\", \"flour\", \"flour\", \"flour\", \"flour\", \"flour\", \"flour\", \"flour\", \"flour\", \"flour\", \"flour\", \"flour\", \"flour\", \"flour\", \"flour\", \"flour\", \"flour\", \"flour\", \"flour\", \"flour\", \"flour\", \"flour\", \"flour\", \"flour\", \"flour"}, {"object": "breechcloth", "object_id": 151, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"Breechcloth\", \"type_name\": \"Object\"},\n\nInput: soap, Output: \n\n{\"type\": \"object\", \"name\": \"Soap\", type_name: \"Object\"},"}, {"object": "bridal_gown", "object_id": 152, "gpt3_output": "\n\n{\"type\": \"item\", \"description\": \"red, with a beading detail\", \"similar objects\": [\"gift certificate\", \"bookmark\", \"cupcake\"]}"}, {"object": "briefcase", "object_id": 153, "gpt3_output": "\n\n{\"type\": \"item\", \"description\": \"black, with a red lid\", \"similar objects\": [\"keyboard\", \"wallet\", \"text book\", \"cheese\"]"}, {"object": "broccoli", "object_id": 154, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "broach", "object_id": 155, "gpt3_output": "\n\nThere are many different objects that can be looked for in objects that are called \"objects\". These objects can be used for their surface features, which are features that a person looks for in objects to see if they are real. The objects that are called \"vegetables\" are things that have a surface feature, such as leaves or flowers. The objects that are called \"beef\" are features on a farm where they are used in cooking. These objects can have any surface feature, as long as it is not the surface feature of the beef itself."}, {"object": "broom", "object_id": 156, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves \"\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "brownie", "object_id": 157, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"Brownie\", \"description\": \"\n\nThe Brownie is a food product that is made from a mixture of sugar and butter. The butter makes the sugar into a spreadable product, and the sugar into a sweetened product. The Brownie has a deep well that allows it to extract liquid sugar from beets, apples, and other vegetables."}, {"object": "brussels_sprouts", "object_id": 158, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylicer, smooth; could have rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"zucchini\", \"Brussels sprouts\"]}"}, {"object": "bubble_gum", "object_id": 159, "gpt3_output": "\n\n{\"type\": \"ingredient\", \"description\": \"\", \"type\": \"diet\", \"has\": [\"ingredient\"]}"}, {"object": "bucket", "object_id": 160, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves \"\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "horse_buggy", "object_id": 161, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for zucchini is its type. The zucchini type should be known so that the model can be able to identify it as such. Additionally, the zucchini type should be smooth so that it will be easy to identify. Finally, it should be possible to have green and rough stems as well as round pieces."}, {"object": "bull", "object_id": 162, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, red, green, yellow\", \"similar objects\": [\"bulldog\", \"chicken\", \"gazelle\"]}"}, {"object": "bulldog", "object_id": 163, "gpt3_output": "\n\n{\"type\": \"dog\", \"description\": \"black, with a red fur\", \"similar objects\": [\"bulldog\", \"cat\", \"chicken\"]}"}, {"object": "bulldozer", "object_id": 164, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, smooth; could have rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"duck\", \"gazelle\", \" elephant\"]}"}, {"object": "bullet_train", "object_id": 165, "gpt3_output": "\n\nThe feature of the bullet train that should focus on for an input with many similar objects is that it can move quickly and be able to carry many people."}, {"object": "bulletin_board", "object_id": 166, "gpt3_output": "\n\n{\"type\": \"text\", \"description\": \"A zucchini can be a vegetable or an animal.\n\" \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "bulletproof_vest", "object_id": 167, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for evidence of an input is the evidence of an input. This means that the model should be able to find evidence of an input if it is used to looking for it. The model should be able to find the evidence of an input if it is seen. This means that the model should be able to find the evidence of an input if it is felt. The model should be able to find the evidence of an input if it is smelled. The model should be able to find the evidence of an input if it is heard."}, {"object": "bullhorn", "object_id": 168, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for signs of life is the animal category. Other features that could be covered include the color of the object, the size of the object, and the shape of the object."}, {"object": "bun", "object_id": 169, "gpt3_output": "\n\n{\"type\": \"cake\", \"description\": \"light brown, dark brown\", \"similar objects\": [\"baked potato\", \"wedge\"]}"}, {"object": "bunk_bed", "object_id": 170, "gpt3_output": "\n\n{\"type\": \"bed\", \"description\": \"round, has a bed sheet on top\", \"similar objects\": [\"bed\", \"towel\", \"curtains\"]}"}, {"object": "buoy", "object_id": 171, "gpt3_output": "\n\n{\"type\": \"noun\", \"description\": \"a container for water or other things\", \"similar objects\": [\"vessel\", \"reinforcement\"]}"}, {"object": "burrito", "object_id": 172, "gpt3_output": "\n\n{\"type\": \"dish\", \"description\": \"pale yellow and black, with a filling\", \"similar objects\": [\"taco\", \"chicken\", \"noodle\"]}"}, {"object": "bus_(vehicle)", "object_id": 173, "gpt3_output": "\n\n{\"type\": \"bus\", \"description\": \"black, red, green, blue\", \"similar objects\": [\"bus\", \"train\", \"car\"]}"}, {"object": "business_card", "object_id": 174, "gpt3_output": "\n\n{\"type\": \"card\", \"description\": \"red; has a card hole in the center\", \"similar objects\": [\"card case\", \"wallet\", \"keyboard\"]"}, {"object": "butter", "object_id": 175, "gpt3_output": "\n\n{\"type\": \"noun\", \"description\": \"fat\", \"term\", \"name\": \"fat\", \"definition\": \"fat\"}"}, {"object": "butterfly", "object_id": 176, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"butterfly\", \"description\": \"black and white, has a wingspan and neck\", \"similar objects\": [\"fairytale\", \" dragon \", \" dragonfly \", \" kite\"]}"}, {"object": "button", "object_id": 177, "gpt3_output": "\n\n{\"type\": \"button\", \"id\": \"-\"}"}, {"object": "cab_(taxi)", "object_id": 178, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"red; has a signage on the side\", \"similar objects\": [\"cab\", \"trolley\", \"bus\"]}"}, {"object": "cabana", "object_id": 179, "gpt3_output": "\n\n{\"type\": \"pool\", \"description\": \"No space left for any other object\", \"similar objects\": [\"house\", \"pool\"]}"}, {"object": "cabin_car", "object_id": 180, "gpt3_output": "\n\nThe object detection model should focus on finding objects with similar characteristics that are in a similar location. The model should also be able to identify different types of objects, such as vegetables and animals."}, {"object": "cabinet", "object_id": 181, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"Cucumber\"},\n{\"type\": \"item\", \"name\": \"Eggplant\"},\n{\"type\": \"item\", \"name\": \"Green Bean\"},\n{\"type\": \"item\", \"name\": \"Cangelo\"},\n{\"type\": \"item\", \"name\": \"Tomato\"},\n\nInput: onion, Output: \n\n{\"type\": \"ingredient\", \"name\": \"Onion\"},\n{\"type\": \"ingredient\", \"name\": \"Mint\"},\n{\"type\": \"ingredient\", \"name\": \""}, {"object": "locker", "object_id": 182, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves \"\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "cake", "object_id": 183, "gpt3_output": "\n\n{\"type\": \"cake\", \"description\": \"light brown, with a light frosting\", \"similar objects\": [\"fruitcake\", \"trucker cake\", \"peanut butter cake\"]}"}, {"object": "calculator", "object_id": 184, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for evidence of life is its ability to identify and track down the sources of its evidence. The model should be able to identify and track down sources of evidence for the existence of life, such as a calculator that has a siren, a ambulance, or a light bulb."}, {"object": "calendar", "object_id": 185, "gpt3_output": "\n\nThe input should focus on specific features that are used to create a complete calendar. The model should be able to identify different days and pages. The pages and days should be clear and easily visible."}, {"object": "calf", "object_id": 186, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black and white stripes; has a long mane\", \"similar objects\": [\"horse\", \"giraffe\", \"elephant\"]}"}, {"object": "camcorder", "object_id": 187, "gpt3_output": "\n\n{\"type\": \"camera\", \"description\": \"round, has a video camera at the top\", \"similar objects\": [\"television\", \" video camera \", \" digital camera ]}"}, {"object": "camel", "object_id": 188, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, or light-colored; has a hump\", \"similar objects\": [\"bison\", \"ox\", \"giraffe\"]}"}, {"object": "camera", "object_id": 189, "gpt3_output": "\n\n{\"type\": \"digital camera\", \"description\": \"round; can be recorded in 3 dimensions\", \"similar objects\": [\"television\", \" video camera \", \" digital camera ]}"}, {"object": "camera_lens", "object_id": 190, "gpt3_output": "\n\n{\"type\": \"image\", \"uuid\": \"cwc4d8b2-c3e0-11e4-8a8b-0050048c2d2\", \"height\": \"image\", \"filename\": \"zucchini.jpg\", \"width\": \"image\", \"caption\": \"zucchini, green, round, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\"}"}, {"object": "camper_(vehicle)", "object_id": 191, "gpt3_output": "\n\nThe feature that should focus on for an ambulance is the siren. The vehicle should focus on the deep handle and the round fruit."}, {"object": "can", "object_id": 192, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "can_opener", "object_id": 193, "gpt3_output": "\n\n{\"type\": \"mechanical tool\", \"description\": \"a tool that opens cans and other containers\", \"similar objects\": [\"pizza\", \"canned food\", \"canned beer\"]}"}, {"object": "candle", "object_id": 194, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \" candle \", \"description\": \"a lighted candle\n\n\"}"}, {"object": "candle_holder", "object_id": 195, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \" candle \", \"description\": \"\n\nThe feature that should focus object detection models for an input with a number of objects equal to or greater than the size of the object being detected."}, {"object": "candy_bar", "object_id": 196, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"Candy Bar\", \"description\": \"\n\n\n\nThe feature that should focus on for an object detection model that is consuming a resource from a resource should be the object's identity. An object's identity should be able to be determined by its features, which should be smooth, cylindrical, and have no rough stems. The model should be able to identify the object's identity and the resources needed to identify the object's identity, which should be a mixture of green and brown stems and round pieces."}, {"object": "candy_cane", "object_id": 197, "gpt3_output": "\n\n{\"type\": \"ingredient\", \"description\": \"\", \"type\": \"yield\", \"yield\": \"\", \"similar objects\": [\"soda\", \"fruit juice\"]}"}, {"object": "walking_cane", "object_id": 198, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is walking a dog is its movement. The model should be able to move the dog body through the environment, moving it from one object to another. The model should also be able to identify different types of objects, such as children, parents, and other members of the family."}, {"object": "canister", "object_id": 199, "gpt3_output": "\n\nThe objects in the input can have features that are similar to those in the output. For example, the zucchini can have smooth cylindrical surfaces, the ambulance can have a shining siren, and the Lantern can have a round light."}, {"object": "canoe", "object_id": 200, "gpt3_output": "\n\n{\"type\": \"boat\", \"description\": \"black, with a red pontoon\", \"similar objects\": [\"canoe\", \"seaweed\", \"taco\", \"chicken\"]}"}, {"object": "cantaloup", "object_id": 201, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "canteen", "object_id": 202, "gpt3_output": "\n\n{\"type\": \"dining room\", \"description\": \"round, with a countertop\", \"similar objects\": [\"cantaloupe\", \"fryer\", \"toaster\"]}"}, {"object": "cap_(headwear)", "object_id": 203, "gpt3_output": "\n\n{\"type\": \"capsule\", \"description\": \"pills, sustenance\", \"similar objects\": [\"baked goods\", \"desserts\", \"beverages\"]}"}, {"object": "bottle_cap", "object_id": 204, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"Bottlecap\", \"id\": \"Bottlecap\", \"position\": 1}"}, {"object": "cape", "object_id": 205, "gpt3_output": "\n\nThe feature that should focus on for an input with a zucchini would be its type: zucchini, while the feature that should focus on for an input with a red wok would be its type: wok."}, {"object": "cappuccino", "object_id": 206, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, smooth; has a little texture\", \"similar objects\": [\"zucchini\", \"carrot\", \"zucchini\"], \"similar objects\": [\"apple\", \"giraffe\", \"elephant\"]}"}, {"object": "car_(automobile)", "object_id": 207, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"black; has a lighted surface\", \"similar objects\": [\"car\", \"truck\", \"carriage\"]"}, {"object": "railcar_(part_of_a_train)", "object_id": 208, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"red; has a track\", \"similar objects\": [\"car\", \"train\", \" locomotive\"]}"}, {"object": "elevator_car", "object_id": 209, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"green; has a floor that goes up and down\", \"similar objects\": [\"ladle\", \"vase\", \"catcher\"]}"}, {"object": "car_battery", "object_id": 210, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"black; has a light engine; could be a car, truck, or bus\", \"similar objects\": [\"car\", \"truck\", \"bus\"]}"}, {"object": "identity_card", "object_id": 211, "gpt3_output": "\n\n{\"type\": \"card\", \"description\": \"KFC.\", \"similar objects\": [\"KFC\", \"card\", \"wallet\", \"frozen food\", \"baked food\", \"dessert\", \"dessert\", \"cake\", \"fruit\", \"fruit\", \"dessert\", \"ingredient\", \"ingredient\", \"ingredient\", \"ingredient\", \"ingredient\", \"ingredient\", \"ingredient\", \"ingredient\", \"ingredient\", \"ingredient\", \"ingredient\", \"ingredient\", \"ingredient\", \"ing"}, {"object": "card", "object_id": 212, "gpt3_output": "\n\n{\"type\": \"card\", \"description\": \"round, has a face down\", \"similar objects\": [\"cardigan\", \"wallet\", \"key\"]"}, {"object": "cardigan", "object_id": 213, "gpt3_output": "\n\n{\"type\": \"article\", \"description\": \"I have a cardigan.\"}, {\"type\": \"article\", \"description\": \"I have a cardigan.\"}, {\"type\": \"article\", \"description\": \"I have a cardigan.\"}, {\"type\": \"article\", \"description\": \"I have a cardigan.\"}, {\"type\": \"article\", \"description\": \"I have a cardigan.\"},"}, {"object": "cargo_ship", "object_id": 214, "gpt3_output": "\n\n{\"type\": \"vessel\", \"description\": \"no description\"}, {\"type\": \"object\", \"description\": \"no description\"}"}, {"object": "carnation", "object_id": 215, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for correlations between two objects is the presence of petals or stalks."}, {"object": "horse_carriage", "object_id": 216, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"red; has a horse and foot on the ground; can be pulled by a horse or a team\", \"similar objects\": [\"carriage\", \" coaches \", \" train \", \" bus \", \" airplane \", \" rocket \", \" satellite \"]"}, {"object": "carrot", "object_id": 217, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"carrot\", \"gazelle\", \"gazelle\", \" elephant\"]}"}, {"object": "tote_bag", "object_id": 218, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"tote bag\", \"description\": \"\n\n\n\nThe feature that should focus on for an input with a lot of change is the object's features. This will include all types of objects, from cylindrical objects to those that have a smooth surface. To find objects that look similar to the object you are looking for, you can use the \"similar objects\" feature."}, {"object": "cart", "object_id": 219, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "carton", "object_id": 220, "gpt3_output": "\n\n{\"type\": \"container\", \"name\": \" Carton \", \"size\": \" \"\", \"content\": \" Carton \", \"shipping charge\": \" \"\", \"logo\": \" Carton \"\", \"weight\": \" \"\", \"bargainness\": \" \"\", \"on Sale\": \"\", \"used In\": \"\", \"on Sale (2)\": \"\", \"used In (2)\": \"\", \"used In (1)\": \"\", \"used In (2)\": \"\", \"used In (1) (2)\": \"\", \"used In (1) (1"}, {"object": "cash_register", "object_id": 221, "gpt3_output": "\n\nThe model should focus on those items that have similar objects as it produces a list of items that are similar to those in the input."}, {"object": "casserole", "object_id": 222, "gpt3_output": "\n\n{\"type\": \"dessert\", \"description\": \"sour cream and jelly\", \"similar objects\": [\"dessert\", \"candy\", \"gummy bear\"]}"}, {"object": "cassette", "object_id": 223, "gpt3_output": "\n\n{\"type\": \"recorded file\", \"name\": \"I'm sorry\", \"filetype\": \"txt\", \"size\": \"\", \"comment\": \"I'm sorry\", \"is_embedded\": true, \"last_comment\": \"I'm sorry\", \"is_saved\": true\", \"type\": \"file\", \"name\": \"I'm sorry\"}"}, {"object": "cast", "object_id": 224, "gpt3_output": "\n\n{\"type\": \"cast\", \"description\": \"round\", \"similar objects\": [\"fiberglass\", \"cast iron\"]}"}, {"object": "cat", "object_id": 225, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black and white, has a long tail\", \"similar objects\": [\"poodle\", \"yorkshire terrier\", \"cat\"]}"}, {"object": "cauliflower", "object_id": 226, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cyan; has a small head and low surface area; can be cooked in the oven\", \"similar objects\": [\"zucchini\", \"carrot\", \"zucchini pipe\"]}"}, {"object": "cayenne_(spice)", "object_id": 227, "gpt3_output": "\n\n{\"type\": \"ingredient\", \"description\": \"Paprika\", \"vibration\": \"spice\", \"taste\": \"tingly\", \"texture\": \"tingly\"},\n\nInput:\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "CD_player", "object_id": 228, "gpt3_output": "\n\n{\"type\": \"audio player\", \"description\": \"round, has a beep sound\", \"similar objects\": [\"play\" \"radio\"]}"}, {"object": "celery", "object_id": 229, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylicer, smooth; could have rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"celery\", \"zucchini\"]}"}, {"object": "cellular_telephone", "object_id": 230, "gpt3_output": "\n\nThere are many different objects that can be used for input, such as objects that are used for growth or for protection. An object that is used for input should be cylindrical, have a smooth surface, and be smooth. There are also many different types of objects, including objects that are used for growth or protection. The different objects that are used for input should be listed as listed above, but some objects may be used for more than one input. For example, an ambulance may be used for both public transportation and for vehicle purposes."}, {"object": "chain_mail", "object_id": 231, "gpt3_output": "\n\n{\"type\": \"chain\", \"description\": \"smooth, has a long end\", \"similar objects\": [\"coaster\", \"maille\", \"chain\"]"}, {"object": "chair", "object_id": 232, "gpt3_output": "\n\n{\"type\": \"chair\", \"description\": \"black and white, has a backrest\", \"similar objects\": [\"furniture\", \"towel\", \"couch\",\"]}"}, {"object": "chaise_longue", "object_id": 233, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"black, smooth; could have bumps and crevices; could be cooked in water or oil\", \"similar objects\": [\"zucchini\", \"chicken\", \"grocery store],"}, {"object": "chalice", "object_id": 234, "gpt3_output": "\n\n{\"type\": \"item\", \"description\": \" stoppable, red, has a hinged lid\", \"similar objects\": [\"coaster\", \"diamond\", \"ruby\"]}"}, {"object": "chandelier", "object_id": 235, "gpt3_output": "\n\n{\"type\": \"chandelier\", \"description\": \"light blue; has a lighted top\", \"similar objects\": [\"chandelier\", \"lamp\"]}"}, {"object": "chap", "object_id": 236, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for candidates like zucchini is the shape of the object. Other features that might be important for this model include the size of the object, the color of the object, and the texture of the object."}, {"object": "checkbook", "object_id": 237, "gpt3_output": "\n\n{\"type\": \"account\", \"description\": \"A checkbook is a book with accounts in each page, each with a different information. The pages are usually written in a journal-like style, with differentdentures and catches. The book has a pad for storing values and a\n\n\"lesson\" for learning new accounts.\""}, {"object": "checkerboard", "object_id": 238, "gpt3_output": "\n\n{\"type\": \"image\", \"image\": [{\"z\": \"2\", \"image\": \"zucchini\", \"title\": \"zucchini\", \"alt\": \"vegetable\", \"size\": \"small\"}, {\"z\": \"3\", \"image\": \"green beans\", \"title\": \"green beans\", \"alt\": \"vegetable\", \"size\": \"small\"}, {\"z\": \"4\", \"image\": \"cucumber\", \"title\": \"cucumber\", \"alt\": \"vegetable\", \"size\": \"small\"}, {\"z\": \"5\", \"image\": \""}, {"object": "cherry", "object_id": 239, "gpt3_output": "\n\n{\"type\": \"fruit\", \"description\": \"red, has a stem\", \"similar objects\": [\"cherry\", \"banana\", \"pear\"]}"}, {"object": "chessboard", "object_id": 240, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\"}, \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]"}, {"object": "chicken_(animal)", "object_id": 241, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black and white stripes; has a long mane\", \"similar objects\": [\"horse\", \"giraffe\", \"elephant\"]}"}, {"object": "chickpea", "object_id": 242, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"chickpea\", \"zucchini\", \"giraffe\"]}"}, {"object": "chili_(vegetable)", "object_id": 243, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "chime", "object_id": 244, "gpt3_output": "\n\n{\"type\": \"audio file\", \"filetype\": \"audio\", \"size\": \"\", \"description\": \"\", \"comment\": \"\", \"embedded\": true, \"preload\": true\", \"preload_prefetch\": true\", \"mute\": true, \"hide\": \"\", \"is_expiry\": \"\", \"mute_prefetch\": true, \"preload_prefetch\": true, \"preload_prefetch_interval\": \"1\", \"interval\": \"solo\", \"interval_solo\": \"1\", \"interval"}, {"object": "chinaware", "object_id": 245, "gpt3_output": "\n\n{\"type\": \"icing tool\", \"description\": \"round; can be made of ice\", \"similar objects\": [\"chocolate\", \"fluffernest\", \"biscuit\"]}"}, {"object": "crisp_(potato_chip)", "object_id": 246, "gpt3_output": "\n\n{\"type\": \"potato\", \"description\": \"round, smooth, has a tough texture\"}, \"similar objects\": [\"zucchini\", \"potato\", \"frozen potato\", \"frozen fruit\", \"frozen drink\", \"frozen food\", \"frozen meal\", \"frozen snack\", \"frozen dessert\", \"frozen action\", \"pet food\", \"pet bed\", \"pet toy\", \"pet food bowl\", \"pet food container\", \"pet food dish\", \"pet food container\", \"pet food box\", \"pet food bag\", \"pet food carton\", \"pet food bag\","}, {"object": "poker_chip", "object_id": 247, "gpt3_output": "\n\n{\"type\": \"token\", \"description\": \"I have this token."}, {"object": "chocolate_bar", "object_id": 248, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"Chocolate Bar\", \"description\": \"\n\nThis object is a chocolate bar. It has a round shape and is made of materials such as paper and light."}, {"object": "chocolate_cake", "object_id": 249, "gpt3_output": "\n\n{\"type\": \"cake\", \"description\": \"light brown, smooth, with a cake texture\", \"similar objects\": [\"graham cheese\", \"chocolate cake\", \"frozen cake\"]}"}, {"object": "chocolate_milk", "object_id": 250, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "chocolate_mousse", "object_id": 251, "gpt3_output": "\n\n{\"type\": \"mousse\", \"composition\", \"name\": \"Chocolate Mousse\"},\n\n{\"type\": \"mousse\", \"composition\", \"name\": \"Mousse de Mango\"},\n\n{\"type\": \"mousse\", \"composition\", \"name\": \"Mousse de G\u00e2teau\"},\n\n{\"type\": \"mousse\", \"composition\", \"name\": \"Mousse de Creme\"},\n\n{\"type\": \"mousse\", \"composition\", \"name\": \"Mousse de Beurre\"},\n\n{\"type\": \"mousse\", \"com"}, {"object": "choker", "object_id": 252, "gpt3_output": "\n\n{\"type\": \"brace\", \"description\": \"smooth, has a small hole in the center\", \"similar objects\": [\"brace\", \"neck\", \"necklace\"]}"}, {"object": "chopping_board", "object_id": 253, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\"}"}, {"object": "chopstick", "object_id": 254, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"small hole in side; could be a piece of candy\", \"similar objects\": [\"chopstick\", \"gummy bear\", \"trucker bar\"]}"}, {"object": "Christmas_tree", "object_id": 255, "gpt3_output": "\n\nThe object detection model should focus on finding objects with similar characteristics that are Christmas-themed."}, {"object": "slide", "object_id": 256, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "cider", "object_id": 257, "gpt3_output": "\n\n{\"type\": \"fruit\", \"description\": \"red, has a stem\", \"similar objects\": [\"apple\", \"banana\", \"pear\"]}"}, {"object": "cigar_box", "object_id": 258, "gpt3_output": "\n\n{\"type\": \"item\", \"description\": \"red, with a lid\", \"similar objects\": [\"box of cigars\", \"candy\", \"keurig coffee maker\"]}"}, {"object": "cigarette", "object_id": 259, "gpt3_output": "\n\n{\"type\": \"instrument\", \"description\": \"earthenware, has a handle\", \"similar objects\": [\"baked potato\", \"cigarette\"]"}, {"object": "cigarette_case", "object_id": 260, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"Cigarette\", \"description\": \"\n\nThe object should focus on those that have similar characteristics. For example, a cigalot could have a stem, while a cigalot case would have a handle and keyhole."}, {"object": "cistern", "object_id": 261, "gpt3_output": "\n\n{\"type\": \"stream\", \"size\": \"\", \"description\": \"\", \"similar objects\": [\"pump\", \"wetlands\", \"iris\"]}"}, {"object": "clarinet", "object_id": 262, "gpt3_output": "\n\nThe Clarinet is a instrument that is used for playing clarinet music."}, {"object": "clasp", "object_id": 263, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"small; has a handle\", \"similar objects\": [\" clasp \", \" claspable tool\"]}"}, {"object": "cleansing_agent", "object_id": 264, "gpt3_output": "\n\nThe type of cleaning agent should be considered in an input for an object detection model."}, {"object": "cleat_(for_securing_rope)", "object_id": 265, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"small, black, has a sharp point\", \"similar objects\": [\"sieve\", \"spade\", \"nail\", \"trowel\"]"}, {"object": "clementine", "object_id": 266, "gpt3_output": "\n\n{\"type\": \"flower\", \"description\": \"red, with a white petal at the top\", \"similar objects\": [\"grape\", \"chocolate\", \"fruitcake\"]}"}, {"object": "clip", "object_id": 267, "gpt3_output": "\n\nClip: round, has a handle, and a clip for a camera."}, {"object": "clipboard", "object_id": 268, "gpt3_output": "\n\nThere are many different objects that can be captured by an object detection model. A model should focus on those objects that are similar to the objects that are being detected. A model also should be able to identify the objects that are being detected by their features and objects that are being detected by their features."}, {"object": "clippers_(for_plants)", "object_id": 269, "gpt3_output": "\n\nThe focus of object detection models should be on those tools that can be used to cut plants or lights."}, {"object": "cloak", "object_id": 270, "gpt3_output": "\n\n{\"type\": \"cloak\", \"function\": \"vanish\", \"description\": \"\"},\n\nInput: soap, Output: \n\n{\"type\": \"soap\", \"function\": \"vanish\", \"description\": \"\"},\n\nInput: rock, Output: \n\n{\"type\": \"rock\", \"function\": \"vanish\", \"description\": \"\"},\n\nInput: rock, Output: \n\n{\"type\": \"rock\", \"function\": \"vanish\", \"description\": \"\"},\n\nInput: rock, Output: \n\n{\"type\": \"rock\", \"function"}, {"object": "clock", "object_id": 271, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for evidence of life is the presence of ticking timepieces. This model should be able to identify objects that share the same structure (like a zucchini or a tomato) and that have the same color (like a tomato or a red apple). Additionally, these models should be able to identify other objects that share a similar structure (like a ambulance or a police car)."}, {"object": "clock_tower", "object_id": 272, "gpt3_output": "\n\nThe input should focus on specific features that the model should be able to detect. For object detection models, these features could include cylindrical or smooth objects, similar objects, or a lightings tool that can be made of papers."}, {"object": "clothes_hamper", "object_id": 273, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"object\", \"description\": \"a hamper of clothes; of a different color than the objects in the input list\"}"}, {"object": "clothespin", "object_id": 274, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"Clothespin\", \"type_name\": \"Object\"},\n\nInput: egg, Output: \n\n{\"type\": \"object\", \"name\": \"Egg\", type_name: \"Object\"},"}, {"object": "clutch_bag", "object_id": 275, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"clutch bag\", \"description\": \"black, with a white logo\", \"similar objects\": [\"purse\", \"bag\", \"key\"]"}, {"object": "coaster", "object_id": 276, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for evidence of life is its ability to run. Coaster models should focus on making the coaster ride fun and exciting, while ambulance models should focus on caring for the object being examined."}, {"object": "coat", "object_id": 277, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"coil\", \"type\": \"material\", \"description\": \"coil, white, long, has a long end\", \"similar objects\": [\"coil\", \"coil of cloth\", \"coil of wax\"]"}, {"object": "coat_hanger", "object_id": 278, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"small hole in the wall\", \"similar objects\": [\"coaster\", \"guitar\", \"teeter-dot\"]"}, {"object": "coatrack", "object_id": 279, "gpt3_output": "\n\n{\"type\": \"platform\", \"description\": \"round, has a handle\", \"similar objects\": [\"bicycle\", \"car\"]}"}, {"object": "cock", "object_id": 280, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, or light-colored; has a head and body\", \"similar objects\": [\"cat\", \"dog\", \"horse\"]}"}, {"object": "cockroach", "object_id": 281, "gpt3_output": "\n\n{\"type\": \"insect\", \"description\": \"black, with a black spot in the center of the body\", \"similar objects\": [\"coon\", \"jaguar\", \"otter\"]}"}, {"object": "cocoa_(beverage)", "object_id": 282, "gpt3_output": "\n\nCoffee, tea, chocolate, milk"}, {"object": "coconut", "object_id": 283, "gpt3_output": "\n\n{\"type\": \"nut\", \"description\": \"green, has a texture and flavor\", \"similar objects\": [\"figs\", \"figs\", \"dried figs\", \"nuts\"]}"}, {"object": "coffee_maker", "object_id": 284, "gpt3_output": "\n\n{\"type\": \"machine\", \"description\": \"round, has a water bottle inside\", \"similar objects\": [\"coffee pot\", \"coffee filter\", \"coffee mug\", \"coffee cup\"]"}, {"object": "coffee_table", "object_id": 285, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"coffee table\", \"description\": \"round, black, has a black surface\", \"similar objects\": [\"coaster\", \"tiramisu\", \"coaster table\"]}"}, {"object": "coffeepot", "object_id": 286, "gpt3_output": "\n\n{\"type\": \"pot\", \"description\": \"red; has a small hole in the center\", \"similar objects\": [\"keurig coffee pot\", \"coffee can\"]}"}, {"object": "coil", "object_id": 287, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for evidence of life is the data of objects. One way to achieve this is to look for objects that have similar characteristics, such as objects that are similar in color, size, or shape. Another way to achieve this is to look for objects that are evidence of recent activity, such as objects that are evidence of a room or room full of objects."}, {"object": "coin", "object_id": 288, "gpt3_output": "\n\n{\"type\": \"coin\", \"price\": 5, \"uniform\": true, \"numeric\": \"1\", \"mintage\": 10, \"iss\": \"1919\", \"mintage_year\": \"1919\", \"mintage_decade\": \"1919\", \"mintage_year_1\": \"1919\", \"mintage_year_2\": \"1919\", \"mintage_decade_1\": \"1919\", \"mintage_year\": \"1919\", \"mintage_year_2\": \"1919\", \"variant\": \"coin\", \"vari"}, {"object": "colander", "object_id": 289, "gpt3_output": "\n\n{\"type\": \"crate\", \"description\": \"black, with a hole in the center\", \"similar objects\": [\"coaster\", \"dishwasher\", \"drummer's goo\"]}"}, {"object": "coleslaw", "object_id": 290, "gpt3_output": "\n\n{\"type\": \"fruit\", \"description\": \"red, has a stem\", \"similar objects\": [\"apple\", \"banana\", \"pear\"]}"}, {"object": "coloring_material", "object_id": 291, "gpt3_output": "\n\nThe features an object that needs to be detected, such as a zucchini or a red pan. Additionally, the model could be used to create illustrations or movies."}, {"object": "combination_lock", "object_id": 292, "gpt3_output": "\n\n{\"type\": \"lock\", \"description\": \"round, has a keyhole\", \"similar objects\": [\"keyboard\", \"couch\", \"barrier\"]}"}, {"object": "pacifier", "object_id": 293, "gpt3_output": "\n\n{\"type\": \"noun\", \"description\": \"a small, small, piece of cloth\", \"usage\",\"archment\", \"noun\"},\n\n{\"type\": \"verb\", \"description\": \"to suck\", \"usage\"},\n\n{\"type\": \"verb\", \"description\": \"to eat\", \"usage\"},\n\n{\"type\": \"verb\", \"description\": \"to stir\", \"usage\"},\n\n{\"type\": \"verb\", \"description\": \"to light\", \"usage\"},\n\nInput: apple, Output: {\"type\": \"fruit\", \"description\": \"red, round, has a stem"}, {"object": "comic_book", "object_id": 294, "gpt3_output": "\n\n{\"type\": \"book\", \"description\": \"The Iliad\", \"similar objects\": [\"bull\", \"bulldog\", \"dragon\"]}"}, {"object": "compass", "object_id": 295, "gpt3_output": "\n\nThe input should be a compass with a smooth surface. The input should also be similar to other objects in the world, such as objects with a siren, a stretcher, or a police car."}, {"object": "computer_keyboard", "object_id": 296, "gpt3_output": "\n\nThe input should be a list of objects, not just one type of object."}, {"object": "condiment", "object_id": 297, "gpt3_output": "\n\nThe features an object should focus on for a zucchini should be round, deep, and has a handle. The features an animal should focus on for a zebra should be black and white stripes, have a long mane, and are likely to have green leaves."}, {"object": "cone", "object_id": 298, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "control", "object_id": 299, "gpt3_output": "\n\nThe features that should be focus for an object detection model that detects objects are cylindrical, smooth, has a stem, and has green and rough stems."}, {"object": "convertible_(automobile)", "object_id": 300, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for potential objects is the object's type. For example, a car would be more likely to find potential objects if it were round, has a smooth surface, and has round headlights."}, {"object": "sofa_bed", "object_id": 301, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"sofia\", \"description\": \"\n\nSofia is a bed and breakfast in the sense that it is a hotel-like room that has been set up to be the home of only one person. The bed and breakfast is also called a \"sofia\" because the owner, Sofia, has written on the door \"sofia is a bed and breakfast\". \n\nThe objects in the room are a sofa bed, a bed, and a bed sheet. The sofa bed is also the only object in the room, and it is made of"}, {"object": "cooker", "object_id": 302, "gpt3_output": "\n\n{\"type\": \"appetizer\", \"description\": \"a small, round, brown or red object\", \"similar objects\": [\"taco\", \"chicken\", \"noodle\", \"noodle bowl\", \"noodle spoon\"]}"}, {"object": "cookie", "object_id": 303, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves \"\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "cooking_utensil", "object_id": 304, "gpt3_output": "\n\n{\"type\": \"ingredient\", \"description\": \"\"},\n\nInput: object, Output:\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "cooler_(for_food)", "object_id": 305, "gpt3_output": "\n\n{\"type\": \"food\", \"description\": \"red; has a shape to it\", \"similar objects\": [\"onion\", \"frozen food\", \"dried food\"]}"}, {"object": "cork_(bottle_plug)", "object_id": 306, "gpt3_output": "\n\n{\"type\": \"Bottle\", \"id\": \"\", \"size\": \"\", \"color\": \"\", \"flavour\": \"\", \"aroma\": \"\", \"aromatica\": \"\", \"pH\": \"\", \"taste\": \"\", \"lack\": \"\", \"composition\": \"\", \"compositione\": \"\", \"lacunes\": \"\", \"lacunese\": \"\", \"aromae\": \"\", \"aromatica\": \"\", \"pH\": \"\", \"taste\": \"\", \"lack\": \"\", \"composition\": \"\", \""}, {"object": "corkboard", "object_id": 307, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"cork\", \"description\": \"round, smooth, has a ring around the edge\", \"similar objects\": [\"fishing net\", \"cork\"]"}, {"object": "corkscrew", "object_id": 308, "gpt3_output": "\n\n{\"type\": \"corkscrew\", \"description\": \"A long, thin piece of metal or plastic that is used to open a wine or other drink\", \"similar objects\": [\"knots\", \"corduroy\", \"flask\"]}"}, {"object": "edible_corn", "object_id": 309, "gpt3_output": "\n\n{\"type\": \"ingredient\", \"description\": \"corn,\u043e \n\", \"similar objects\": [\"corniche\", \"mashed potatoes\", \"wedge potatoes\"]}"}, {"object": "cornbread", "object_id": 310, "gpt3_output": "\n\n{\"type\": \"dessert\", \"description\": \"sugar, corn, and spice mixture; has a corn tortilla as the crust\", \"similar objects\": [\"taco\", \"mango\", \"chocolate cake\"]}"}, {"object": "cornet", "object_id": 311, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for potential objects is its ability to find potential objects. potential objects are people, things, or events that may be similar to the object being looked for. The model should be able to identify potential objects and should be able to perform tasks such as setting up the object detection model and/oront the potential objects."}, {"object": "cornice", "object_id": 312, "gpt3_output": "\n\n{\"type\": \"building\", \"location\", \"architecture\", \"geographical\", \"coordinates\", \"similar objects\": [\"cornice\", \"tower\", \"island\"]}"}, {"object": "cornmeal", "object_id": 313, "gpt3_output": "\n\n{\"type\": \"ingredient\", \"description\": \"corn; meal; salt; oil; baking soda\", \"similar objects\": [\"cornhusker\" \"dried corn\"]}"}, {"object": "corset", "object_id": 314, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves \"\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "costume", "object_id": 315, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \" Costume \", \"description\": \"A Costume \n\nAn object that is currently in use."}, {"object": "cougar", "object_id": 316, "gpt3_output": "\n\n{\"type\": \" animal \", \"description\": \"light brown fur; fur is long and wiry\", \"similar objects\": [\"cat\", \"dog\", \"catcher\", \"yacht\"]}"}, {"object": "coverall", "object_id": 317, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"coverall\", \"description\": \"A coverall is a type of clothing that is often used for cold weather. It is made of heavy fabric or cloth and is usually worn with a coat to keep the person warm.\""}, {"object": "cowbell", "object_id": 318, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for clues about its surroundings is the object's or object's body. This includes any smooth, cylindrical shapes, as well as those that have rough stems and have bumps or ridges on their surface. That includes both round and rough objects, such as zucchini and ambulance vehicles. That includes looking for clues about the model's surroundings, such as how the object looks in light or by using a light source."}, {"object": "cowboy_hat", "object_id": 319, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"round, black, has a symbol on the front\", \"similar objects\": [\" cowboy hat \", \" cowboy coat \", \" cowboy boots \"]"}, {"object": "crab_(animal)", "object_id": 320, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that detects objects is its ability to identify objects. Object detection models that are able to identify objects should be able to identify more objects in an input such as a zucchini or crab."}, {"object": "crabmeat", "object_id": 321, "gpt3_output": "\n\nCrabmeat is a type of meat that is made from crab meat."}, {"object": "cracker", "object_id": 322, "gpt3_output": "\n\n{\"type\": \"ingredient\", \"description\": \"sugar\", \"similar objects\": [\" cracker \", \" cake \", \" pie \"], \"similar objects\": [\"onion \", \"gravy \", \"cache\", \"cache case\"]"}, {"object": "crape", "object_id": 323, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "crate", "object_id": 324, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves \"\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "crayon", "object_id": 325, "gpt3_output": "\n\n{\"type\": \"image\", \"image\": \"zucchini.png\", \"size\": \"small\", \"created\": \"2009-01-12 02:00:00\", \"updated\": \"2009-01-12 02:00:00\"}, \"zucchini.png"}, {"object": "cream_pitcher", "object_id": 326, "gpt3_output": "\n\n{\"type\": \"pouring tool\", \"description\": \"green; has a handle\", \"similar objects\": [\"tiramisu\", \"chocolate milk\", \"frozen cream\"]}"}, {"object": "crescent_roll", "object_id": 327, "gpt3_output": "\n\n{\"type\": \"dessert\", \"description\": \"sour cream and jelly\", \"similar objects\": [\"sour cream\", \"jelly\", \"cranberry\"]"}, {"object": "crib", "object_id": 328, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves \"\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "crock_pot", "object_id": 329, "gpt3_output": "\n\n{\"type\": \"food\", \"description\": \"red; has a pot inside it; can be cooked in the oven\", \"similar objects\": [\"pot\", \"dishwasher\", \"fridge\", \"freeze\"]}"}, {"object": "crossbar", "object_id": 330, "gpt3_output": "\n\n{\"type\": \"couple\", \"description\": \"round, has a sharp end\", \"similar objects\": [\"dishwasher\", \"washer\", \"drummer's chair\"]}"}, {"object": "crouton", "object_id": 331, "gpt3_output": "\n\nThere are many different objects an object detection model could focus on, such as animals, vegetables, tools, and machines."}, {"object": "crow", "object_id": 332, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\"},\n\n{\"type\": \"vegetable\", \"name\": \"cyndle\", \"sharpeness\"},\n\n{\"type\": \"object\", \"name\": \"crazed ambulance\"},\n\n{\"type\": \"vehicle\", \"name\": \"red; has a siren\"},\n\n{\"type\": \"vegetable\", \"name\": \"banana\", \"round\"},\n\n{\"type\": \"vegetable\", \"name\": \"pear\", \"green\"},\n\n\":{\"type\": \"object\", \"name\":"}, {"object": "crowbar", "object_id": 333, "gpt3_output": "\n\n{\"type\": \"tool\", \"description\": \"round, has a handle\", \"similar objects\": [\"harpoon\", \"nailbrush\", \"tape measure\"]"}, {"object": "crown", "object_id": 334, "gpt3_output": "\n\n{\"type\": \"title\", \"description\": \"Object Detection Models for Vegetables and Fruits\", \"authors\": [\"Donald A. downing\", \"John R. uping\", \"Donald A.\", \"John R.\", \"academic\", \"academic\", \" Donald A. downing\", \"John R. uping\", \"academic\", \"academic\", \" Donald A. downing\", \"John R. uping\", \"academic\", \"academic\", \" John R. uping\", \"academic\", \"academic\", \"academic\", \"academic\", \"academic\","}, {"object": "crucifix", "object_id": 335, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for crucifixes is their style. This model should be able to find crucifixes that have similar objects on them, such as papers and lights."}, {"object": "cruise_ship", "object_id": 336, "gpt3_output": "\n\n{\"type\": \"vessel\", \"description\": \"no description\"}, {\"type\": \"person\", \"description\": \"no description\"}, {\"type\": \"object\", \"description\": \"no description\"}, {\"type\": \"paramotor\", \"description\": \"no description\"}, {\"type\": \"machine\", \"description\": \"no description\"}, {\"type\": \"chamber\", \"description\": \"no description\"}, {\"type\": \"vessel\", \"description\": \"no description\"}, {\"type\": \"person\", \"description\": \"no description\"}, {\"type\": \"object\", \"description\": \"no description\"}, {\"type\": \"param"}, {"object": "police_cruiser", "object_id": 337, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"red; has a shining mirror; could have a broken window\", \"similar objects\": [\"car\", \"truck\", \"vans\"]}"}, {"object": "crumb", "object_id": 338, "gpt3_output": "\n\n{\"type\": \"ingredient\", \"name\": \"Cream\", \"description\": \"\"},\n\n{\"type\": \"ingredient\", \"name\": \"Bread\", \"description\": \"\"},\n\n{\"type\": \"ingredient\", \"name\": \"Bread\", \"description\": \"\"},\n\n{\"type\": \"ingredient\", \"name\": \"Bread\", \"description\": \"\"},\n\n{\"type\": \"ingredient\", \"name\": \"Bread\", \"description\": \"\"},\n\n{\"type\": \"ingredient\", \"name\": \"Bread\", \""}, {"object": "crutch", "object_id": 339, "gpt3_output": "\n\n{\"type\": \"weapon\", \"description\": \"black, with a red handle\", \"similar objects\": [\"wedge\", \"thorn\", \"axle\", \"axle\", \" crutch ],\n"}, {"object": "cub_(animal)", "object_id": 340, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "cube", "object_id": 341, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, smooth; has a rough stem; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "cucumber", "object_id": 342, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "cufflink", "object_id": 343, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"small, metal, has a handle\", \"similar objects\": [\"ring\", \"watch\"]"}, {"object": "cup", "object_id": 344, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"Cup\", \"description\": \"Cup with a handle\", \"similar objects\": [\"Soup pot\", \"Soup can\", \"Souvenir cup\"]}"}, {"object": "trophy_cup", "object_id": 345, "gpt3_output": "\n\n{\"type\": \"cup\", \"description\": \"green, has a handle\", \"similar objects\": [\"cup\", \"cupcake\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\", \"cup\","}, {"object": "cupboard", "object_id": 346, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"coaster\", \"description\": \"black, smooth, has a handle\", \"similar objects\": [\"coaster\", \"eskimo\", \"poster\", \"cupboard\"]}"}, {"object": "cupcake", "object_id": 347, "gpt3_output": "\n\n{\"type\": \"cake\", \"description\": \"yellow, has a ring around the center\", \"similar objects\": [\"cake\", \"cup\", \"cupcake\"]}"}, {"object": "hair_curler", "object_id": 348, "gpt3_output": "\n\n{\"type\": \"apparatus\", \"description\": \"round, has a light at the end of it\", \"similar objects\": [\"coaster\", \"golf ball\", \"treadmill\"]}"}, {"object": "curling_iron", "object_id": 349, "gpt3_output": "\n\n{\"type\": \"curling iron\", \"description\": \"a tool used for curling hair\", \"similar objects\": [\"irons\", \"ironsingle\", \"ironside\"]}"}, {"object": "curtain", "object_id": 350, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, smooth; could have rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "cushion", "object_id": 351, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"Cushion\", \"description\": \"Cushion; shape; size; color; material; design; what is it?\"}"}, {"object": "cylinder", "object_id": 352, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "cymbal", "object_id": 353, "gpt3_output": "\n\nThe cymbal is a musical instrument that can be used for playing music or making noises."}, {"object": "dagger", "object_id": 354, "gpt3_output": "\n\n{\"type\": \"weapon\", \"description\": \"black; has a sharp blade\", \"similar objects\": [\"dagger\", \"spear\", \" Hunting knife \n\n\"}"}, {"object": "dalmatian", "object_id": 355, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black and white stripes; has a long mane\", \"similar objects\": [\" Dalmatian \", \"houngean\", \"kangaroo\"]}"}, {"object": "dartboard", "object_id": 356, "gpt3_output": "\n\n{\"type\": \"game\", \"description\": \"Eggs with No Name\", \"similar objects\": [\"pumpkin\", \"banana\"]}"}, {"object": "date_(fruit)", "object_id": 357, "gpt3_output": "\n\n{\"type\": \"date\", \"date\", \"time\", \"year\", \"time zone\", \"time zone offset\", \"time zone offset\", \"time zone\", \"time zone code\", \"time zone code\", \"time zone\", \"delta\", \"delta\", \"time zone\", \"time zone\", \"delta\", \"offset\", \"offset\", \"time zone\", \"time zone\", \"time zone\", \"delta\", \"time zone\", \"time zone\", \"delta\", \"time zone\", \"delta\", \"time zone\", \"delta\", \"time zone\", \"time zone\", \""}, {"object": "deck_chair", "object_id": 358, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \" Deck Chair \", \"description\": \"A chair that is used for sitting on. It has a long back, a noose, and two lead wires to a gun. The chair has also been used as a place to put something in front of it to make it look like it is solid. \"\n\"},"}, {"object": "deer", "object_id": 359, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, red; could have hooves\", \"similar objects\": [\"giraffe\", \" deer \", \"ox\"]}"}, {"object": "dental_floss", "object_id": 360, "gpt3_output": "\n\nThe objects in the input could be dental floss. The objects in the output could be a dental floss."}, {"object": "desk", "object_id": 361, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"object\", \"description\": \"\"}"}, {"object": "detergent", "object_id": 362, "gpt3_output": "\n\n{\"type\": \" Detergent\", \"description\": \"A detergent is a liquid detergent that helps to clean dishes quickly and easily."}, {"object": "diaper", "object_id": 363, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \" diaper \", \"description\": \" a small, round, black object with a white spot in the center\", \"similar objects\": [\"paprika\", \"seaweed\", \"grits\"]}"}, {"object": "diary", "object_id": 364, "gpt3_output": "\n\n{\"type\": \"textbook\", \"description\": \"The model should focus on objects that are similar in size, shape, or color to the input. For example, the zucchini should have a similar shape and color to the cucumber, while the eggplant should have a similar green to the green bean. The light tool should be able to light up with a siren, while the Lantern should be able to light up with a light tool that has a light tool."}, {"object": "die", "object_id": 365, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for clues about is its surroundings. This model should be able to identify different types of objects, such as cylindrical objects, smooth objects, and round objects. It should also be able to identify different types of objects, such as Cyndrical objects, green objects, and round objects."}, {"object": "dinghy", "object_id": 366, "gpt3_output": "\n\n{\"type\": \"vessel\", \"description\": \"is a boat; has a net at the bow\", \"similar objects\": [\"shorewatch\", \"seaweed\", \"buddy\"]"}, {"object": "dining_table", "object_id": 367, "gpt3_output": "\n\n{\"type\": \"table\", \"description\": \"black, with a white top\", \"similar objects\": [\"coaster\", \"coaster system\", \"coaster lot\", \"coaster mint\"]}"}, {"object": "tux", "object_id": 368, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "dish", "object_id": 369, "gpt3_output": "\n\n{\"type\": \"dish\", \"description\": \"red, smooth, has a handle\", \"similar objects\": [\"ice cream\", \"frozen yogurt\", \"banana\"]"}, {"object": "dish_antenna", "object_id": 370, "gpt3_output": "\n\nThe input should focus on features that are specific to the dish antenna input, such as a round body, small size, and a clear plastic cover. The output should focus on features that are specific to the lightening input, such as a round body, large size, and a clear plastic cover."}, {"object": "dishrag", "object_id": 371, "gpt3_output": "\n\n{\"type\": \"dishwasher\", \"description\": \"black, has a small hole in the center\", \"similar objects\": [\"pantry\", \"fridge\", \"freeze\", \"microwave\", \"dishwasher\", \"washer\", \"sink\", \"washer\", \"irons\", \"sink\", \"iron\", \"pan\", \"stove\", \"stove\", \"fire\", \"lamp\", \"lamp\", \"lamp\", \"lamp\", \"lamp\", \"lamp\", \"lamp\", \"lamp\", \"lamp\", \"lamp\", \"l"}, {"object": "dishtowel", "object_id": 372, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"dishtowel\", \"description\": \"round, black, has a series of small nooks\", \"similar objects\": [\"coaster\", \"sink\", \"tape measure\"]}"}, {"object": "dishwasher", "object_id": 373, "gpt3_output": "\n\n{\"type\": \"washing machine\", \"description\": \"green and blue; has a drain\", \"similar objects\": [\"sink\", \" dishwasher \", \" washing machine \"}"}, {"object": "dishwasher_detergent", "object_id": 374, "gpt3_output": "\n\n{\"type\": \" Detergent\", \"description\": \"Red; has a siren; can beocytheic\"},\n\n{\"type\": \" Dishwasher\", \"description\": \"Blue; has a non-stick coating\"},\n\n{\"type\": \" Dishes \", \"description\": \"Canned chicken; has a lot of spices\"},\n\n{\"type\": \" Kitchen \", \"description\": \"Paleo chicken and bacon\", \"similar objects\": [\"paleo chicken\", \"paleo bacon\", \"scrambled eggs\", \"scrambled bacon\", \"scrambled chicken\"],\n\n}"}, {"object": "dispenser", "object_id": 375, "gpt3_output": "\n\n{\"type\": \"vitamin\", \"description\": \" Needs to be able to dispense a given amount of product; needs to be able to dispense a given amount of water; needs to be able to dispense a given amount of oil; needs to be able to dispense a given amount of water\n\n\n\nInput: can, Output:\n\n{\"type\": \"beef\", \"description\": \"round, has a handle\", \"similar objects\": [\"chicken\", \"pork\"]}"}, {"object": "diving_board", "object_id": 376, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, smooth; has a small hole in the middle\", \"similar objects\": [\"zucchini\", \"apple\", \"giraffe\"]}"}, {"object": "Dixie_cup", "object_id": 377, "gpt3_output": "\n\n{\"type\": \"cup\", \"description\": \"red; has a handle and a handle top\", \"similar objects\": [\"coaster\", \"dishwasher\", \"coaster\"]"}, {"object": "dog", "object_id": 378, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black and white, has a long mane\", \"similar objects\": [\"horse\", \"giraffe\", \"elephant\"]}"}, {"object": "dog_collar", "object_id": 379, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"dog\", \"description\": \"black and white, has a wagging tail\", \"similar objects\": [\"cat\", \"catcher\", \"poodle\"]}"}, {"object": "doll", "object_id": 380, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"Doll\", \"description\": \"\n\nAn object that is either a doll or a toy."}, {"object": "dollar", "object_id": 381, "gpt3_output": "\n\n{\"type\": \"currency\", \"description\": \"the United States dollar\", \"similar objects\": [\"dollar\", \"ruin\", \"gift\"]}"}, {"object": "dollhouse", "object_id": 382, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"Dollhouse\", \"description\": \"Dollhouse is a house that is used as a place for playtime in the dollhouse. It is a small, two-story structure with a small open floor plan. The dollhouse has four rooms that can be used for playtime for the players in the room. There is a small door that leads to the attic where the players can store items. The dollhouse is made of wood and plastic. It is a fun place for the players to play in and the players can play with their friends."}, {"object": "dolphin", "object_id": 383, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, or green; has a long tail\", \"similar objects\": [\" dolphin \", \"whale \", \"seaweed\"]}"}, {"object": "domestic_ass", "object_id": 384, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black and white, could have a tail\", \"similar objects\": [\"pig\", \"cat\", \"toucan\"]}"}, {"object": "doorknob", "object_id": 385, "gpt3_output": "\n\n{\"type\": \"door handle\", \"description\": \"thick, dark, has a handle\", \"similar objects\": [\"keyboard\", \"couch\", \"barrier\"]}"}, {"object": "doormat", "object_id": 386, "gpt3_output": "\n\nThere are many different features an object detection model could focus on, such as detecting that an object is round, has a handle, or is made of papers."}, {"object": "doughnut", "object_id": 387, "gpt3_output": "\n\n{\"type\": \"doughnut\", \"description\": \"a small, round, golden doughnut\", \"similar objects\": [\"biscuit\", \"trundleberry\", \"kebab\"]}"}, {"object": "dove", "object_id": 388, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, smooth; could have rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"duck\", \"gazelle\"]}"}, {"object": "dragonfly", "object_id": 389, "gpt3_output": "\n\nThe input should be a creature that can be detected by object detection models. This model should be able to walk, run, and fly. The model should also have a headlight and a dragonfly wingspan."}, {"object": "drawer", "object_id": 390, "gpt3_output": "\n\n{\"type\": \"item\", \"description\": \"red; has a handle\", \"similar objects\": [\"door\", \"cups of coffee\", \"cake\", \"frozen food\"]}"}, {"object": "underdrawers", "object_id": 391, "gpt3_output": "\n\n{\"type\": \"instrument\", \"description\": \"xylophone\", \"similar objects\": [\"guitar\", \"banjo\"]}"}, {"object": "dress", "object_id": 392, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"Dress\", \"type\": \"vegetable\", \"description\": \"Cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\"}"}, {"object": "dress_hat", "object_id": 393, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"white; has a brimmed hat\", \"similar objects\": [\"hat\", \"sunglasses\"]}"}, {"object": "dress_suit", "object_id": 394, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"white; has a strap\", \"similar objects\": [\"sunglasses\", \"hat\"]}"}, {"object": "dresser", "object_id": 395, "gpt3_output": "\n\n{\"type\": \"table\", \"description\": \"round, has a lot ofslaught of ingredients\", \"similar objects\": [\"cat\", \"trucker\", \"SUV\"]}"}, {"object": "drill", "object_id": 396, "gpt3_output": "\n\n{\"type\": \"tool\", \"description\": \"round, has a handle\", \"similar objects\": [\"crown\", \"spade\", \"jigsaw\", \"borer\"],"}, {"object": "drone", "object_id": 397, "gpt3_output": "\n\nThere are many different objects that can be looked for in objects that have been identified as zucchini, such as the fact that they are cylindrical, smooth, and have green leaves. Additionally, they could be sliced into round pieces, and had green leaves."}, {"object": "dropper", "object_id": 398, "gpt3_output": "\n\nThere are many different features an object detection model could focus on, such as detecting that an object is a fruit, detecting that an object is a object that can be cooked, or lightening speed."}, {"object": "drum_(musical_instrument)", "object_id": 399, "gpt3_output": "\n\n{\"type\": \"drum\", \"description\": \"round, has a beat that can be heard over the noise of the environment\", \"similar objects\": [\"drummer\", \"harp\"]}"}, {"object": "drumstick", "object_id": 400, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cyan; has a thin stalk; can be peeled\", \"similar objects\": [\"zucchini\", \"melon\"]}"}, {"object": "duck", "object_id": 401, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"duck\", \"gazelle\", \"rhinoceros\"]}"}, {"object": "duckling", "object_id": 402, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black and white, could have a duckbill\"}, \"similar objects\": [\" duck \", \" duckling \", \" duck \", \" duckling \", \" duck \", \" duck \", \" duck \", \" duck \", \" duck \", \" duck \", \" duck \",\" duck \", \" duck \", \" duck \", \" duck \", \" duck \", \" duck \", \" duck \", \" duck \", \" duck \", \" duck \", \" duck \",\" duck \", \" duck \", \" duck \", \" duck \", \" duck \", \" duck \", \" duck \", \" duck \", \" duck \", \" duck \", \" duck \", \""}, {"object": "duct_tape", "object_id": 403, "gpt3_output": "\n\n{\"type\": \"text\", \"message\": \"This is a message\", \"similar objects\": [\"tape\", \"tape measure\", \"tape measureR\"]"}, {"object": "duffel_bag", "object_id": 404, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"duffel bag\", \"description\": \"\"}"}, {"object": "dumbbell", "object_id": 405, "gpt3_output": "\n\n{\"type\": \"dumbbell\", \"description\": \"dwarf, has a small head\", \"similar objects\": [\"dwarf tomato\", \"dwarf apple\"]}"}, {"object": "dumpster", "object_id": 406, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves \"\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "dustpan", "object_id": 407, "gpt3_output": "\n\n{\"type\": \"instrument\", \"description\": \"has a cloth top; can be emptied by hand\", \"similar objects\": [\"sink\", \"bowl\", \"pan\", \"coaster\"]}"}, {"object": "eagle", "object_id": 408, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, or green; has a beak and beady eyes\", \"similar objects\": [\"giraffe\", \"monkey\", \"toucan\"]}"}, {"object": "earphone", "object_id": 409, "gpt3_output": "\n\n{\"type\": \"audio\", \"description\": \"round, has a hole in the middle\", \"similar objects\": [\"microwave\", \" Skype \"]"}, {"object": "earplug", "object_id": 410, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"\"}"}, {"object": "earring", "object_id": 411, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"small; has a soundless sound\", \"similar objects\": [\"ring\", \"ringtone\"]}"}, {"object": "easel", "object_id": 412, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves \"\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "eclair", "object_id": 413, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for candidates for a meal is the object's type. For example, an object that is called an \"object\" is typically considered for a meal because it has an object type of \"object.\""}, {"object": "eel", "object_id": 414, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for zucchini is its type. This model should be able to identify zucchini as a food item. Additionally, the model should be able to identify zucchini as an animal or as a tool that can be used for cooking or as a vehicle for transportation."}, {"object": "egg", "object_id": 415, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "egg_roll", "object_id": 416, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"egg\", \"grocery store\", \"green beans\"]}"}, {"object": "egg_yolk", "object_id": 417, "gpt3_output": "\n\n{\"type\": \"noun\", \"description\": \"the egg yolk\", \"similar objects\": [\"chicken\", \"egg\"]}"}, {"object": "eggbeater", "object_id": 418, "gpt3_output": "\n\n{\"type\": \"mechanical tool\", \"description\": \"round, has a handle\", \"similar objects\": [\"screwdriver\", \"pump\"]"}, {"object": "eggplant", "object_id": 419, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "electric_chair", "object_id": 420, "gpt3_output": "\n\n{\"type\": \"toy\", \"description\": \"red; has a chair with a light at the end of it\", \"similar objects\": [\"electric chair\", \"toy box\", \"tape measure\"]"}, {"object": "refrigerator", "object_id": 421, "gpt3_output": "\n\n{\"type\": \"implement\", \"description\": \" needs a door to open and a handle to open, Output: {\"type\": \"result\", \"result\": \"closed\"}"}, {"object": "elephant", "object_id": 422, "gpt3_output": "\n\nThe feature that should focus on for an elephant is their fur. The fur on an elephant is smooth, and the animal has green and brown stripes."}, {"object": "elk", "object_id": 423, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, or green; has a antlers\", \"similar objects\": [\"elk\", \"giraffe\", \" elephant \", \"horse\"]}"}, {"object": "envelope", "object_id": 424, "gpt3_output": "\n\nThe input should be a probability space with features. A model that focuses on features should be more efficient in analyzing an input with many features."}, {"object": "eraser", "object_id": 425, "gpt3_output": "\n\nThere are many different features an object detection model could focus on, such as detecting objects of different sizes, detecting shapes, and detecting the presence of specific objects."}, {"object": "escargot", "object_id": 426, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"escargot\", \"gazelle\", \" elephant\"]}"}, {"object": "eyepatch", "object_id": 427, "gpt3_output": "\n\nThe objects in the input can be either objects (vegetables, animals, tools, etc.), or names (zucchini, red apple, banana, etc.).\n\nThe objects in the input can also be specific objects, such as \"cucumber\" or \"giraffe\"."}, {"object": "falcon", "object_id": 428, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, or light-colored; has a beak, neck, and wings\", \"similar objects\": [\" Falcon \", \" Falcon \", \"Canon\", \"Lion \", \"Giraffe \", \" elephant \"], \"fraudulent objects\": [\"Falcon \"], \"forgotten objects\": [\"Falcon \"], \"aliens\": [\"Falcon \"], \"forbidden objects\": [\"Falcon \"], \"abandoned objects\": [\"Falcon \"], \"ghosts\": [\"Falcon \"], \"forgotten friends\": [\"Falcon \""}, {"object": "fan", "object_id": 429, "gpt3_output": "\n\n{\"type\": \"instrument\", \"description\": \"round, has a motor\", \"similar objects\": [\"kite\", \"rotor\", \"motorcycle\"]}"}, {"object": "faucet", "object_id": 430, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"round; has a handle\", \"similar objects\": [\"faucet\", \"ink bottle\", \"cup\"]}"}, {"object": "fedora", "object_id": 431, "gpt3_output": "\n\n{\"type\": \"headwear\", \"description\": \"black, with a red band\", \"similar objects\": [\"sunglasses\", \"hat\", \"bunny earrings\"]}"}, {"object": "ferret", "object_id": 432, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cyan; has a short stem; can run\", \"similar objects\": [\"gazelle\", \"otter\", \"island\", \"octopus\"]}"}, {"object": "Ferris_wheel", "object_id": 433, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, smooth; could have rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"apple\", \"giraffe\", \"banana\"]}"}, {"object": "ferry", "object_id": 434, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for ferry objects is the shape of the object. Other features that might be important for this model include the size of the object, the color of the object, and the texture of the object."}, {"object": "fig_(fruit)", "object_id": 435, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"fig\", \"grape\", \"grapefruit\"]}"}, {"object": "fighter_jet", "object_id": 436, "gpt3_output": "\n\n{\"type\": \"aircraft\", \"description\": \"black, white, red, blue\", \"similar objects\": [\"jet\", \"lion\", \" 747 \", \" Stallard \n\n\"}"}, {"object": "figurine", "object_id": 437, "gpt3_output": "\n\n{\"type\": \"figurine\", \"description\": \"black, white, red, green, blue\", \"similar objects\": [\"puppy\", \"dog\", \"cat\"]}"}, {"object": "file_cabinet", "object_id": 438, "gpt3_output": "\n\n{\"type\": \"file\", \"name\": \"file\", \"size\": \"\", \"similar objects\": [\"file\", \"cabinet\", \"drawer\", \"barrel\"]"}, {"object": "file_(tool)", "object_id": 439, "gpt3_output": "\n\n{\"type\": \"file\", \"name\": \"file.txt\", \"size\": \"\", \"description\": \"\"},\n\n\"type\": \"file\", \"name\": \"file_store.txt\", \"size\": \"\", \"description\": \"\"},"}, {"object": "fire_alarm", "object_id": 440, "gpt3_output": "\n\nThe feature that should focus on for an ambulance is the siren. The fire alarm could be focused on if the machine is made of firewood or of a more durable material."}, {"object": "fire_engine", "object_id": 441, "gpt3_output": "\n\nThe ambulance should focus on the round vehicle and the fire engine on the light lamp."}, {"object": "fire_extinguisher", "object_id": 442, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for fire extinguishers is the models's ability to find them. The model should be able to find extinguishers by looking for patterns in the data. This is done by using a particular set of algorithms that can identify which extinguisher is the model's target."}, {"object": "fire_hose", "object_id": 443, "gpt3_output": "\n\n{\"type\": \"stream\", \"description\": \"red; has a flow rate of 1.2 ounces per minute\", \"similar objects\": [\"guitar player\", \"smoke\"]"}, {"object": "fireplace", "object_id": 444, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for fireplaces is the type of fireplace. This should look for fires that have a round or cylindrical shape, with smooth or rough stems, and has green or brown skin."}, {"object": "fireplug", "object_id": 445, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"clearance; has a release button\", \"similar objects\": [\"grenade\", \"bomb\"]}"}, {"object": "first-aid_kit", "object_id": 446, "gpt3_output": "\n\nThere are many different objects that can be used with first-aid, such as a knife, a pen, and a phone. These objects can be used for many different purposes, such as for communication, for healing, and for other tasks."}, {"object": "fish", "object_id": 447, "gpt3_output": "\n\n{\"type\": \"fish\", \"description\": \"black, white, small; could be fleshed out\", \"similar objects\": [\"giraffe\", \" dolphin \", \" \n  \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \"\", \""}, {"object": "fish_(food)", "object_id": 448, "gpt3_output": "\n\n{\"type\": \"fish\", \"description\": \"a type of fish\", \"similar objects\": [\"giraffe\", \" dolphin \", \" \n\" \n\"\", \"\", \"\"}"}, {"object": "fishbowl", "object_id": 449, "gpt3_output": "\n\n{\"type\": \"pool\", \"description\": \"No depths are given\"}, {\"type\": \"pool\", \"depth\": 10}"}, {"object": "fishing_rod", "object_id": 450, "gpt3_output": "\n\n{\"type\": \"item\", \"description\": \"green, has a handle\", \"similar objects\": [\"fishing net\", \"rod\", \"linefinder\"]}"}, {"object": "flag", "object_id": 451, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for flags is its ability to identify objects with flags as their only feature. This object detection model would be able to identify objects with flags as their only feature, such as a flag for objects that have a cylindrical shape, green color, and smooth surface."}, {"object": "flagpole", "object_id": 452, "gpt3_output": "\n\nThe feature that should focus on for an input with a flag is the object's object type. For an input with a wok, for example, the object type would be \"vegetable.\""}, {"object": "flamingo", "object_id": 453, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"orange and black; has a long neck\", \"similar objects\": [\"flamingo\", \"parrot\", \"giraffe\"]}"}, {"object": "flannel", "object_id": 454, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"Flannel\", \"quantity\": \"1\", \"similar objects\": [\"flannel\", \"paper\", \"lightbulb\"]}"}, {"object": "flap", "object_id": 455, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for Vegetables is whether or not the object is cylindrical. The object should also be smooth, with no rough stems. The model should be able to slice Vegetables into round pieces and green leaves."}, {"object": "flash", "object_id": 456, "gpt3_output": "\n\n{\"type\": \"image\", \"uuid\": \"cwc8c_8c_ading\", \"size\": \"small\", \"created\": \"2013-06-14 00:00:00\", \"lastseen\": \"2013-08-10 00:00:00\"}, \"image_2\": \"http://www.w3.org/TR/2000/GLs-xpath.xpath\", \"image_3\": \"http://www.w3.org/TR/2000/GLs-xpath.xpath\", \"image_4\": \"http://www.w"}, {"object": "flashlight", "object_id": 457, "gpt3_output": "\n\n{\"type\": \"light tool\", \"description\": \"round; could be made of papers\", \"similar objects\": [\"lamp\", \"flashlight\", \"candle\"]"}, {"object": "fleece", "object_id": 458, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"fleece\", \"description\": \"red; has a fleece\", \"similar objects\": [\"cat\", \"coaster\", \" dog\"]}"}, {"object": "flip-flop_(sandal)", "object_id": 459, "gpt3_output": "\n\nThe flip-flop is a two-state machine, where in state 0 it is without any features. In state 1 the flip-flop has all the features of a regular flip-flop and can turn on and off."}, {"object": "flipper_(footwear)", "object_id": 460, "gpt3_output": "\n\nThere are many different types of object detection models that could be used for an input of zucchini, apple, ambulance, lightening, and flipper."}, {"object": "flower_arrangement", "object_id": 461, "gpt3_output": "\n\n{\"type\": \"flower arrangement\", \"arrangement\", \"color\", \"description\"},\n\n\"type\": \"flower arrangement\", \"arrangement\", \"color\", \"description\"},"}, {"object": "flute_glass", "object_id": 462, "gpt3_output": "\n\nThe input should be a natural product that can be used to create products such as flutes and flutes glass."}, {"object": "foal", "object_id": 463, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for potential objects is its ability to find potential objects. potential objects are things that the model could be able to see if it were to find them. potential objects could be things that the model is potential to find. For example, the model could be able to find objects that are made of paper or lights."}, {"object": "folding_chair", "object_id": 464, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for evidence of an input is the ability to see objects. For example, an object detection model that is looking for evidence of a zucchini will be looking for objects that have the type of object \"zucchini\"."}, {"object": "food_processor", "object_id": 465, "gpt3_output": "\n\n{\"type\": \"food\", \"description\": \"red; has a texture like paper\", \"similar objects\": [\"potato\", \"frozen food\", \"baked food\"]}"}, {"object": "football_(American)", "object_id": 466, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for evidence of an object is its type. An object detection model that is looking for evidence of an object will focus on objects that have the type \"vegetable\"."}, {"object": "football_helmet", "object_id": 467, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"Football Helmet\", \"id\": \"\", \"position\": 1, \"content\": \"\n\nThis helmet is perfect for any football fan!\n\n\"}, {\"type\": \"item\", \"name\": \"Football Helmet\", \"id\": \"\", \"position\": 2, \"content\": \"\n\nThis helmet is perfect for any football fan!\n\n\"}, {\"type\": \"item\", \"name\": \"Football Helmet\", \"id\": \"\", \"position\": 3, \"content\": \"\n\nThis helmet is perfect for any football fan!\n\n\"}, {\"type\":"}, {"object": "footstool", "object_id": 468, "gpt3_output": "\n\n{\"type\": \"table\", \"description\": \"black, with a black top and bottom, and a pair of black legs; can be placed to one side or the other\", \"similar objects\": [\"tray\", \"curtis\", \"tennis ball\"]}"}, {"object": "fork", "object_id": 469, "gpt3_output": "\n\n{\"type\": \"appetizer\", \"description\": \"1\", \"type\": \"dessert\", \"type2\": \"cake\", \"similar objects\": [\"frozen yogurt\", \"frozen fruit\", \"frozen vegetables\"]}"}, {"object": "forklift", "object_id": 470, "gpt3_output": "\n\n{\"type\": \"tool\", \"description\": \"round, has a handle\", \"similar objects\": [\"fork\", \"cane\", \"machinery\"]"}, {"object": "freight_car", "object_id": 471, "gpt3_output": "\n\n{\"type\": \"car\", \"description\": \"black, with a red stripe down the middle\", \"similar objects\": [\"car\", \"trolley\", \"bus\"]}"}, {"object": "French_toast", "object_id": 472, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for food is its size. Other features that might be important for an object detection model to focus on include its shape, color, and size."}, {"object": "freshener", "object_id": 473, "gpt3_output": "\n\n{\"type\": \"ingredient\", \"name\": \"Water\"},\n\n{\"type\": \"product\", \"description\": \"Fruit\"},\n\n{\"type\": \"product\", \"description\": \"Vegetables\"},\n\n{\"type\": \"product\", \"description\": \"Household items\"},\n\nInput: onion, Output: \n\n{\"type\": \"ingredient\", \"name\": \"Salt\"},\n\n{\"type\": \"product\", \"description\": \"Chips\"},\n\n{\"type\": \"product\", \"description\": \"Chips\"},\n\nInput: onion, Output: \n"}, {"object": "frisbee", "object_id": 474, "gpt3_output": "\n\n{\"type\": \"football\", \"description\": \"black and red; could have yellow and blue fields\", \"similar objects\": [\"soccer ball\", \"soccer ball],"}, {"object": "frog", "object_id": 475, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black and white, has a long mane\", \"similar objects\": [\"toucan\", \"seagull\", \"whale\"]}"}, {"object": "fruit_juice", "object_id": 476, "gpt3_output": "\n\n{\"type\": \"dietary\", \"description\": \"nothing\", \"similar objects\": [\"soda\", \"fruit juice\"]}"}, {"object": "frying_pan", "object_id": 477, "gpt3_output": "\n\n{\"type\": \"frying pan\", \"description\": \"round, deep; has a deep handle\", \"similar objects\": [\"chopstick\", \"dishwasher\", \"crate\"]"}, {"object": "fudge", "object_id": 478, "gpt3_output": "\n\n{\"type\": \"dessert\", \"description\": \"sugar, nuts\", \"similar objects\": [\"fudge brown\", \"fudge brown sugar\", \"fudge sugar\"]"}, {"object": "funnel", "object_id": 479, "gpt3_output": "\n\n{\"type\": \"vase\", \"description\": \"light green; has a lip\", \"similar objects\": [\"gazelle\", \"fowl\"]}"}, {"object": "futon", "object_id": 480, "gpt3_output": "\n\n{\"type\": \"tent\", \"description\": \"round, with a hole in the center, has a light on top\", \"similar objects\": [\"tent\", \"patio\", \"tentpole\"]"}, {"object": "gag", "object_id": 481, "gpt3_output": "\n\n{\"type\": \"instrument\", \"description\": \"round, has a sound box\", \"similar objects\": [\"instruments\", \"saxon\", \"flute\"]}"}, {"object": "garbage", "object_id": 482, "gpt3_output": "\n\nThe input should be a list of features that includes an object's type, description, and similar objects."}, {"object": "garbage_truck", "object_id": 483, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"black, red, yellow; could have a blue and red stripe\", \"similar objects\": [\"dumpster\", \"dump\", \"truck\"]}"}, {"object": "garden_hose", "object_id": 484, "gpt3_output": "\n\n{\"type\": \"supplier\", \"description\": \"red, with a long nozzle\", \"similar objects\": [\"spoon\", \"iaan\", \"iaan can\"]}"}, {"object": "gargle", "object_id": 485, "gpt3_output": "\n\n{\"type\": \"gulp\", \"description\": \"water\", \"similar objects\": [\"soup\", \"tongue\"]}"}, {"object": "gargoyle", "object_id": 486, "gpt3_output": "\n\n{\"type\": \"servo\", \"description\": \"a creature with a gargantuan size; has a long neck\", \"similar objects\": [\"giant cockroach\", \"chicken\", \"tronchie\", \"toad\"]"}, {"object": "garlic", "object_id": 487, "gpt3_output": "\n\nThe focus of object detection models should be on those foods that have specific features that are shared by all objects in the input. For example, garlic might be a food that has a round shape and deep colors. This would be the focus of the model for that food."}, {"object": "gasmask", "object_id": 488, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for gasmasks is their color. This will include models that are looking for vehicles with gasmasks, models that were found with gasmasks, and models that are currently being used with gasmasks."}, {"object": "gazelle", "object_id": 489, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, and red; has a mane of black and white stripes\", \"similar objects\": [\"gazelle\", \"kangaroo\", \"elk\"]}"}, {"object": "gelatin", "object_id": 490, "gpt3_output": "\n\nThe input could be a single object, like a ball of candy. The output could be a list of objects, like a list of fruits. The similar objects in the list could be different objects, like a different ball of candy."}, {"object": "gemstone", "object_id": 491, "gpt3_output": "\n\n{\"type\": \"gem\", \"description\": \"pink, with a white birthstone inside\", \"similar objects\": [\"sapphire\", \" turquoise \", \" turquoise \"\", \" sapphire \"\", \" turquoise \"\", \" sapphire \"\", \" turquoise \"\", \" sapphire \"\", \" turquoise \"\", \" sapphire \"\", \" turquoise \"\", \" turquoise \"\", \" sapphire \"\", \" turquoise \"\", \" turquoise \"\", \" sapphire \"\", \" turquoise \"\", \" tur"}, {"object": "generator", "object_id": 492, "gpt3_output": "\n\nThe input should be a machine that creates things like lights and generators. These machines should be able to create different types of light, like sirens or lights for a police department."}, {"object": "giant_panda", "object_id": 493, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, or green; has a mane of long, thin sheets\", \"similar objects\": [\"panda\", \"chicken\", \"goat\"]}"}, {"object": "gift_wrap", "object_id": 494, "gpt3_output": "\n\n{\"type\": \"gift\", \"description\": \"round, smooth, has a bow\", \"similar objects\": [\"chocolate\", \"chopstick\", \"necklace\"]}"}, {"object": "ginger", "object_id": 495, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for smells of zucchini is turning it into a zucchini zucchini. The model should also be able to turn zucchini into zucchini zucchini."}, {"object": "giraffe", "object_id": 496, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black and white stripes; has a long mane\", \"similar objects\": [\"horse\", \"giraffe\", \"elephant\"]}"}, {"object": "cincture", "object_id": 497, "gpt3_output": "\n\n{\"type\": \"brace\", \"description\": \"a metal bandage\", \"similar objects\": [\"bracelet\", \"bracelet case\"]}"}, {"object": "glass_(drink_container)", "object_id": 498, "gpt3_output": "\n\n{\"type\": \"container\", \"name\": \"wine\", \"description\": \"\n\nThe object detection model should focus on objects that have the same name as the input. For example, a glass drink container would be a good input for an object detection model that focuses on this type of objects."}, {"object": "globe", "object_id": 499, "gpt3_output": "\n\nThe input should be a sphere with a smooth surface."}, {"object": "glove", "object_id": 500, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "goat", "object_id": 501, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black and white stripes; has a long mane\", \"similar objects\": [\"horse\", \"giraffe\", \"elephant\"]}"}, {"object": "goggles", "object_id": 502, "gpt3_output": "\n\nThe objects in the input could be in any order, but the features that should be focused on in an input about a goggles are to make the model more realistic, to make it easy to see, and to make it easy to find the objects."}, {"object": "goldfish", "object_id": 503, "gpt3_output": "\n\n{\"type\": \"fish\", \"description\": \"black and white, with a small tail\", \"similar objects\": [\"giraffe\", \"otter\", \"coaster\"]"}, {"object": "golf_club", "object_id": 504, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for Golf Clubs is their size. Other features that the model should look for include being of a specific size, having a specific shape, and having a specific light or dark color."}, {"object": "golfcart", "object_id": 505, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"light blue; has aiardic motor; could have tarmac or road surfaces\", \"similar objects\": [\" golfcart \", \" car \", \" truck \", \" bike \", \" scooter \"]"}, {"object": "gondola_(boat)", "object_id": 506, "gpt3_output": "\n\n{\"type\": \"watercraft\", \"description\": \"green, with a stem and boat-like body\", \"similar objects\": [\"coaster\", \"raft\", \"yacht\"]}"}, {"object": "goose", "object_id": 507, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, or green; has a beak and a neck\", \"similar objects\": [\"poodle\", \"comet\", \"feline cat\", \"cat\", \"otter\"]}"}, {"object": "gorilla", "object_id": 508, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black and white stripes; has a long mane\", \"similar objects\": [\"horse\", \"giraffe\", \"elephant\"]}"}, {"object": "gourd", "object_id": 509, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylicer, smooth; could have rough stems; could be intoxted and undercooked)\", \"similar objects\": [\"zucchini\", \"zucchinibag\", \"frozen zucchini\"]"}, {"object": "grape", "object_id": 510, "gpt3_output": "\n\n{\"type\": \"grape\", \"name\": \"Grape\", \"size\": \"small\", \"description\": \"Cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\"}"}, {"object": "grater", "object_id": 511, "gpt3_output": "\n\n{\"type\": \"grater\", \"description\": \"round, has a sharp blade\", \"similar objects\": [\"zucchini\", \"carrot\", \"sticker\", \"flour\", \"salt\"]}"}, {"object": "gravestone", "object_id": 512, "gpt3_output": "\n\n{\"type\": \" Grave \", \"Description\": \"\n\nThe Grave object model should focus on features that are cylindrical, smooth, and have a green color. The similar objects model should focus on features that are a similar object to the Grave object model, including a cylindrical shape, smooth color, and similar symptoms."}, {"object": "gravy_boat", "object_id": 513, "gpt3_output": "\n\n{\"type\": \"vessel\", \"description\": \"black, white, clear; could have been used for shipping goods\", \"similar objects\": [\"ship\", \"wok\", \"pot\", \"catcher\"]}"}, {"object": "green_bean", "object_id": 514, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "green_onion", "object_id": 515, "gpt3_output": "\n\n{\"type\": \"noun\", \"description\": \"a small, fresh onion\", \"usage\": \"verb\", \"term\", \"definition\": \"\n\nA fresh onion is a type of onion that is not from onions."}, {"object": "griddle", "object_id": 516, "gpt3_output": "\n\n{\"type\": \"dish\", \"description\": \"round, has a non-stick surface\", \"similar objects\": [\"onion\", \"butterfly\", \"butterfly egg\"]}"}, {"object": "grill", "object_id": 517, "gpt3_output": "\n\n{\"type\": \" grill \", \"description\": \"a tool used to cook food\", \"similar objects\": [\"grill\", \"grill\", \"stove\", \" oven \", \" stove top \"]"}, {"object": "grits", "object_id": 518, "gpt3_output": "\n\n{\"type\": \"textbook\", \"description\": \"A book with every page turned, so that the reader can only see the title and the first few lines,\" \"similar objects\": [\"page\", \"textbook\"]}"}, {"object": "grizzly", "object_id": 519, "gpt3_output": "\n\n{\"type\": \" mammal \", \"name\": \"grizzly bear \", \"size\": \"0-1\", \"description\": \"\", \"similar objects\": [\"bison\", \" elk \", \" elk \", \" elk \", \" bison \", \"bison\", \"bison \", \"bison \", \"bison \", \"bison \", \"grizzly bear \", \"grizzly bear \", \"grizzly bear \", \"grizzly bear \", \"grizzly bear \", \"grizzly bear \", \"grizzly bear \", \"g"}, {"object": "grocery_bag", "object_id": 520, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves \"\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "guitar", "object_id": 521, "gpt3_output": "\n\nThe input should be a specific, known object. The output should be an object that is similar to the input."}, {"object": "gull", "object_id": 522, "gpt3_output": "\n\n{\"type\": \"wing\", \"description\": \"fully feathered\", \"similar objects\": [\" Falcon \"],"}, {"object": "gun", "object_id": 523, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for evidence of life is its ability to identify similar objects. An object detection model that is looking for evidence of life should be able to identify that an object is a medical device, such as a gun, because it is filled with lead and has a siren."}, {"object": "hairbrush", "object_id": 524, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"Hairbrush\", \"type\": \"object\"}, {\"type\": \"object\", \"name\": \"Hairbrush\", \"type\": \"object\"}, {\"type\": \"object\", \"name\": \"Hairbrush\", \"type\": \"object\"}, {\"type\": \"object\", \"name\": \"Hairbrush\", \"type\": \"object\"}, {\"type\": \"object\", \"name\": \"Hairbrush\", \"type\": \"object\"}, {\"type\": \"object\", \"name\": \"Hairbrush\", \"type\": \"object\"}, {\"type\": \"object\","}, {"object": "hairnet", "object_id": 525, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"round; has a filter\", \"similar objects\": [\"hat\", \"sunglasses\", \"sunglasses case\"]}"}, {"object": "hairpin", "object_id": 526, "gpt3_output": "\n\n{\"type\": \"angle\", \"description\": \"from behind; could be anpherd's cross or shepherd's cross with out front, has short legs\", \"similar objects\": [\"cornerstone\", \"harpoon\", \"arcade\"]}"}, {"object": "halter_top", "object_id": 527, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black and white stripes; has a long mane\", \"similar objects\": [\"horse\", \"giraffe\", \"elephant\"]}"}, {"object": "ham", "object_id": 528, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, red, green, blue\", \"similar objects\": [\"hamster\", \"giraffe\", \" elephant \", \"cat\"]}"}, {"object": "hamburger", "object_id": 529, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black and white stripes; has a long mane\", \"similar objects\": [\"horse\", \"giraffe\", \"elephant\"]}"}, {"object": "hammer", "object_id": 530, "gpt3_output": "\n\n{\"type\": \"tool\", \"description\": \"round, has a handle\", \"similar objects\": [\"mace\", \"fishing net\", \"linefinder\"]}"}, {"object": "hammock", "object_id": 531, "gpt3_output": "\n\n{\"type\": \"bed\", \"description\": \"soft, down-filled; could be made of straw\", \"similar objects\": [\"couch\", \"towel\"]"}, {"object": "hamper", "object_id": 532, "gpt3_output": "\n\n{\"type\": \"room\", \"description\": \"small, roomy; has a small area for storage\", \"similar objects\": [\"bathroom\", \"bedroom\", \" living room \", \" kitchen \", \" garage \", \" outdoor room \", \" outdoor space \", \"\n\n\"size\", \"location\", \"ventilation\", \"covers\", \"mattress\", \"Refrigerator\", \"washer and dryer\", \"Refrigerator with ice\", \"Refrigerator with ice and water\", \" washer and dryer with ice\", \"Refrigerator with water\", \"Refrigerator with water and ice\","}, {"object": "hamster", "object_id": 533, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black and white, has a short tail\", \"similar objects\": [\"hamster\", \"poodle\", \"cat\"]}"}, {"object": "hair_dryer", "object_id": 534, "gpt3_output": "\n\nThe features that should be focus for an object detection model that smells zucchini should be:\n\n-Sliced zucchini\n-A smooth zucchini\n-Can have brown and rough stems\n-Green zucchini\n-Zebra zucchini\n-Dented zucchini\n-Shredded zucchini\n-Dried up zucchini\n-Bumpy zucchini\n\nThe features that should be focus for an object detection model that smells vegetables should be:\n\n-A cylindrical zucchini\n-A smooth zucchini\n-A d"}, {"object": "hand_glass", "object_id": 535, "gpt3_output": "\n\nThe objects in the input can be of different types:\n\nObjects can be of different types, such as vegetables, animals, and tools."}, {"object": "hand_towel", "object_id": 536, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"Wok\", \"description\": \"round, deep, has a handle\", \"similar objects\": [\"pan\", \"pot\", \"frying pan\"]}"}, {"object": "handcart", "object_id": 537, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"black; has a red stripe down the middle\", \"similar objects\": [\"car\", \"trolley\", \"bank\"]}"}, {"object": "handcuff", "object_id": 538, "gpt3_output": "\n\n{\"type\": \"crime\", \"description\": \"selling arms and drugs\", \"similar objects\": [\"misdelivered package\", \" drug deal \", \" Fugitive \", \" Fugitive from jail \", \" Fugitive from prison \", \" Terrorist \", \" Terrorist group \", \" associate of terrorist \", \" associate of terrorist \", \" associate of terrorist group \", \" associate of associate of terrorist \", \" associate of associate of terrorist group \", \" associate of associate of terrorist group \", \" associate of associate of terrorist group \", \" associate of associate of terrorist group \", \" associate of associate of terrorist group \", \" associate of associate of terrorist group \","}, {"object": "handkerchief", "object_id": 539, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"handkerchief\", \"type\": \"object\"}, {\"type\": \"object\", \"name\": \"handkerchief\", \"type\": \"object\"},"}, {"object": "handle", "object_id": 540, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"handle\", \"description\": \"I have a handle to an ambulance.\n\nsimilar objects\": [\"pump\", \"pumpkin\", \"frying pan\", \"stainless steel pan\", \"pan\", \"fry pan\", \"dish pan\", \"casserole pan\", \"gazebo pan\", \"coaster pan\", \"trucker pan\", \"canopy\"]"}, {"object": "handsaw", "object_id": 541, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for Vegetables is whether or not the object is cylindrical. The object is also should have a smooth surface as well as rough stems and leaves."}, {"object": "hardback_book", "object_id": 542, "gpt3_output": "\n\n{\"type\": \"book\", \"description\": \"black, smooth, has a cover of smooth black leather\", \"similar objects\": [\"leather bookcase\", \"coffee table\", \"coaster\"]"}, {"object": "harmonium", "object_id": 543, "gpt3_output": "\n\n{\"type\": \"instrument\", \"description\": \"guitar, brass, wood\", \"similar objects\": [\"fountain\", \"banjo\", \"banter\"]}"}, {"object": "hat", "object_id": 544, "gpt3_output": "\n\n{\"type\": \"item\", \"description\": \"green, with a small hole in the center\", \"similar objects\": [\"hat\", \"turban\"]}"}, {"object": "hatbox", "object_id": 545, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"Hat\", \"quantity\": \"1\", \"description\": \"Hat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat\n\nHat"}, {"object": "veil", "object_id": 546, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "headband", "object_id": 547, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"Headband\", \"type\": \"object\"}, {\"type\": \"object\", \"name\": \"Headband\", \"type\": \"object\"}, {\"type\": \"object\", \"name\": \"Headband\", \"type\": \"object\"},"}, {"object": "headboard", "object_id": 548, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"headboard\", \"description\": \"round, black, has a black finish\", \"similar objects\": [\"nightstand\", \"bedframe\", \"nightstick\"]"}, {"object": "headlight", "object_id": 549, "gpt3_output": "\n\nThe features that should be focus for an object detection model that smells like an apple would be the round body and the siren sound. Additionally, an ambulance would want to focus on the color and the bright light that the light has."}, {"object": "headscarf", "object_id": 550, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"black, white, or light green; has a band around the head\", \"similar objects\": [\"hat\", \" scarf \", \" scarf-holder\"]}"}, {"object": "headset", "object_id": 551, "gpt3_output": "\n\n{\"type\": \"audio device\", \"description\": \"round, has a speaker\", \"similar objects\": [\"headset\", \"microwave\", \"television\"]}"}, {"object": "headstall_(for_horses)", "object_id": 552, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"red; has a horseshoe on the front, black on the back\", \"similar objects\": [\"horse\", \"carriage\", \"horse carriage\"]}"}, {"object": "heart", "object_id": 553, "gpt3_output": "\n\n{\"type\": \"card\", \"description\": \"red; has a hole in the center\", \"similar objects\": [\"pump\", \"pump\", \"cartridge\", \"coaster\", \"magazine\", \"tron\", \"watch\"]"}, {"object": "heater", "object_id": 554, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"round, has a lighted area\", \"similar objects\": [\"warmonger\", \"flammable material\", \"fire starter\"]"}, {"object": "helicopter", "object_id": 555, "gpt3_output": "\n\n{\"type\": \"aviation\", \"description\": \"red; has a wingspan and height\", \"similar objects\": [\"pilots\", \"bomber\", \" Sukhoi \", \"C-130\"]}"}, {"object": "helmet", "object_id": 556, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for potential objects is its ability to find potential objects. potential objects are things that the model could be able to see if it were to encounter them in the world. potential objects could be things that the model could be able to eat, such as fruits and vegetables. potential objects could also be things that the model could be able to run away from, such as a ambulance or a car."}, {"object": "heron", "object_id": 557, "gpt3_output": "\n\n{\"type\": \"fish\", \"description\": \"black, white, and green; has a long neck\", \"similar objects\": [\"giraffe\", \"whale\", \"seagull\"]}"}, {"object": "highchair", "object_id": 558, "gpt3_output": "\n\n{\"type\": \"trucker\", \"description\": \"round, has a handle\", \"similar objects\": [\"tank\", \"car\"]"}, {"object": "hinge", "object_id": 559, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, smooth; has a sharp, jagged edge\", \"similar objects\": [\"gazelle\", \"gazelle\", \" horse \", \" elephant \", \" camel \"], \"similar objects\": [\"apple\", \"banana\", \"pear\", \"gazelle\", \" elephant \", \" camel \"], \"similar objects\": [\"fry\", \"pan\", \"fry pan\", \"frying pan\", \"pot\", \"pan\", \"coaster\", \"scope\", \"scope\", \"scope\", \"scope\", \"scope\", \"scope\","}, {"object": "hippopotamus", "object_id": 560, "gpt3_output": "\n\n{\"type\": \"livestock\", \"description\": \"a type of animal that is killed and cooked for food\", \"similar objects\": [\"baboon\", \"giraffe\", \" elephant \", \" camels \"],"}, {"object": "hockey_stick", "object_id": 561, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, smooth; could have rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"honeydew\", \"honey\", \"grape\"]}"}, {"object": "hog", "object_id": 562, "gpt3_output": "\n\n{\"type\": \"livestock\", \"description\": \"red; has a short horn and long horns; could have four-wheel drive\", \"similar objects\": [\"ox\", \"giraffe\", \"chicken\", \"toucan\"]}"}, {"object": "home_plate_(baseball)", "object_id": 563, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"name\": \"home plate\", \"description\": \"\", \"similar objects\": [\"baseball\", \"bat\", \"ball\"]}"}, {"object": "honey", "object_id": 564, "gpt3_output": "\n\n{\"type\": \"noun\", \"description\": \"noun\", \"verb\": \"verb\", \"verb\", \"noun\"},\n\n\"noun\", \"verb\": \"verb\", \"verb\", \"noun\"},\n\n\"noun\", \"verb\": \"verb\", \"verb\", \"noun\"},"}, {"object": "fume_hood", "object_id": 565, "gpt3_output": "\n\nThe features that should be focus for an object detection model that smells like zucchini would be the model's ability to identify zucchini as a food item, the model's ability to identify zucchini as a source of light, and the model's ability to identify zucchini as a source of Fume Hood."}, {"object": "hook", "object_id": 566, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves \"\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "hookah", "object_id": 567, "gpt3_output": "\n\n{\"type\": \" Smoking article \", \"description\": \"No description provided \", \"similar objects\": [\"hookah\", \"hookah device\"]"}, {"object": "hornet", "object_id": 568, "gpt3_output": "\n\n{\"type\": \"object\", \"description\": \"a small, black, round, no wings\", \"similar objects\": [\"coaster\", \"tronco\", \"giant ball of ice\", \"sky\")}"}, {"object": "horse", "object_id": 569, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black and white stripes; has a long mane\", \"similar objects\": [\"horse\", \"giraffe\", \"elephant\"]}"}, {"object": "hose", "object_id": 570, "gpt3_output": "\n\n{\"type\": \"supplier\", \"description\": \"\", \"status\": \"active\"}, \"object\":[]"}, {"object": "hot-air_balloon", "object_id": 571, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cyan, smooth; has a Narrow and Slicedourgeous surface\", \"similar objects\": [\"apple\", \"grape\", \"canary\"]}"}, {"object": "hotplate", "object_id": 572, "gpt3_output": "\n\n{\"type\": \"food\", \"description\": \"red, has a handle\", \"similar objects\": [\"taco\", \"chicken\", \"noodle\"]}"}, {"object": "hot_sauce", "object_id": 573, "gpt3_output": "\n\n{\"type\": \"ingredient\", \"description\": \"salt and pepper\", \"similar objects\": [\"salt and pepper\", \"salt and pepper\", \"onion\"]}"}, {"object": "hourglass", "object_id": 574, "gpt3_output": "\n\n{\"type\": \"angle\", \"angle\": (0\u00b0, 0\u00b0), \"description\": \"depends on the input\", \"similar objects\": [\"hourglass\", \"zodiacal light\", \"moon\"]}"}, {"object": "houseboat", "object_id": 575, "gpt3_output": "\n\n{\"type\": \"watercraft\", \"description\": \"black, with a red stripe down the middle\", \"similar objects\": [\"coaster\", \"seaweed\", \"gulf island\", \"rivers\"]}"}, {"object": "hummingbird", "object_id": 576, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"honeydew\", \"thorny bush\", \"grape\"]}"}, {"object": "hummus", "object_id": 577, "gpt3_output": "\n\n{\"type\": \"dietary\", \"description\": \"salt, olive, lemon, garlic\", \"similar objects\": [\"tahini\", \"sour cream\", \"onion\"]}"}, {"object": "polar_bear", "object_id": 578, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, or light-colored; has a fur; could have a furrow on its back\", \"similar objects\": [\"polar bear\", \"elk\", \"indigo cat\", \"island\"]}"}, {"object": "icecream", "object_id": 579, "gpt3_output": "\n\n{\"type\": \"food\", \"description\": \"red, with a white spot in the center\", \"similar objects\": [\"frozen yogurt\", \"chocolate milk\", \"frozen fruit\", \"frozen vegetables\", \"frozen meat\", \"frozen cheese\", \"frozen milk\", \"frozen yogurt\", \"frozen meat and cheese\", \"frozen vegetables and meat\", \"frozen meat and cheese\", \"frozen fruit\", \"frozen vegetables and meat\", \"frozen meat and cheese\", \"frozen vegetables and meat\", \"frozen meat and cheese\", \"frozen vegetables and meat\", \""}, {"object": "popsicle", "object_id": 580, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, smooth; has a smooth surface; could be filled with ice or water\", \"similar objects\": [\"popsicle\", \"ice cream\", \"frozen yogurt\"]}"}, {"object": "ice_maker", "object_id": 581, "gpt3_output": "\n\n{\"type\": \"item\", \"description\": \"red, with a top and bottom that come together to form a U-shape; can be made of metal\", \"similar objects\": [\"frozen yogurt\", \"frozen fruit\", \"frozen vegetables\"]}"}, {"object": "ice_pack", "object_id": 582, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"ice pack\", \"type\": \"object\"}, {\"type\": \"object\", \"name\": \"ice pack\", \"type\": \"object\"},"}, {"object": "ice_skate", "object_id": 583, "gpt3_output": "\n\n{\"type\": \"skate\", \"description\": \"A skateboarder boards a skateboard through the ice\", \"similar objects\": [\"ice cream\", \"skate\", \"iceberg\"]}"}, {"object": "igniter", "object_id": 584, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for fire is the input type. For this model, the zucchini would be an object with type \"vegetable\"."}, {"object": "inhaler", "object_id": 585, "gpt3_output": "\n\nThe features that should be focus for an object detection model that smells like zucchini would be the model's ability to identify zucchini as a food item, the model's ability to identify zucchini as a source of light, and the model's ability to identify zucchini as a source of nutrition."}, {"object": "iPod", "object_id": 586, "gpt3_output": "\n\n{\"type\": \"audio player\", \"description\": \"round, has a beep sound\", \"similar objects\": [\"playground\", \"microwave\", \"microwave toy\"]}"}, {"object": "iron_(for_clothing)", "object_id": 587, "gpt3_output": "\n\n{\"type\": \"metal\", \"description\": \"black; has a sharp edge\", \"similar objects\": [\"copper\", \"steel\"]}"}, {"object": "ironing_board", "object_id": 588, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"ironing board\", \"description\": \"round, has a handle, and a cloth cover\"}, {\"type\": \"object\", \"name\": \"ironing board\", \"description\": \"black, has a handle, and a cloth cover\"}, {\"type\": \"object\", \"name\": \"ironing board\", \"description\": \"smooth, has a handle, and a cloth cover\"}, \"similar objects\": [\"ironing board\", \"iron\", \"board\", \"cloth\", \"cover\", \"handle\", \"sink\", \"frame\", \"surface\", \"substrate\","}, {"object": "jacket", "object_id": 589, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"Jacket\", \"id\": \"\", \"position\": 1, \"price\": \"\", \"backpack\", \"purse\", \"amulet\", \"fairytale\", \"necklace\", \"amethyst\", \"bronze\", \"cape\", \"gun\", \"amethyst\", \"bronze\", \"cape\", \"amulet\", \"fairytale\", \"necklace\", \"amethyst\", \"bronze\", \"cape\", \"amulet\", \"fairytale\", \"necklace\", \"amethyst\", \"bronze\", \"cape\","}, {"object": "jam", "object_id": 590, "gpt3_output": "\n\n{\"type\": \"dessert\", \"description\": \"sour cream\", \"similar objects\": [\"dessert\", \"chocolate\", \"fruitcake\"]}"}, {"object": "jar", "object_id": 591, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"Sour cream\", \"description\": \"\n\nSour cream is a food product that is made from a cheese that is melted and then spread in a jar. Jars are often used as a forte of food items such as yogurt and yogurt bowls."}, {"object": "jean", "object_id": 592, "gpt3_output": "\n\n{\"type\": \"person\", \"description\": \"black, white, red; could have body shape and posture\", \"similar objects\": [\"fisherman\", \"pigeon\", \"seagull\"]}"}, {"object": "jeep", "object_id": 593, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"red; has a bright light; can have a light up only when driving\", \"similar objects\": [\"car\", \"truck\", \"camper\", \"camper\", \"sled\"]}"}, {"object": "jelly_bean", "object_id": 594, "gpt3_output": "\n\n{\"type\": \"noun\", \"description\": \"jelly\", \"usage\": \"noun\"}\n\nInput: jelly, Output:\n\n{\"type\": \"noun\", \"description\": \"jelly\", \"usage\": \"noun\"}"}, {"object": "jersey", "object_id": 595, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \" jersey\", \"description\": \"red; could have a number of colors\", \"similar objects\": [\"satchel\", \"watch\", \" necklace\"]}"}, {"object": "jet_plane", "object_id": 596, "gpt3_output": "\n\n{\"type\": \"aircraft\", \"description\": \"black, white, and red; has a wingspan; can fly\", \"similar objects\": [\"jet\", \"lion\", \"trucker\", \"buffalo\"]"}, {"object": "jewel", "object_id": 597, "gpt3_output": "\n\n{\"type\": \"gem\", \"description\": \"pink, with a clear top\", \"similar objects\": [\"sapphire\", \" turquoise \", \"sapphire\"]}"}, {"object": "jewelry", "object_id": 598, "gpt3_output": "\n\n{\"type\": \"jewelry\", \"description\": \"round, has a bezel or front piece\", \"similar objects\": [\"wafer\", \"coil\", \"bronze\", \"ferrara\"]}"}, {"object": "joystick", "object_id": 599, "gpt3_output": "\n\n{\"type\": \"adventure\", \"description\": \"round, has a handle, can be used for swimming\", \"similar objects\": [\"x-wing\", \"star wars\" ]}"}, {"object": "jumpsuit", "object_id": 600, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"jumpsuit\", \"description\": \"A jumpsuit is a clothing item that is used for professional wrestling and other activities\"."}, {"object": "kayak", "object_id": 601, "gpt3_output": "\n\n{\"type\": \"boat\", \"description\": \"black, with a white stripe running down the middle\", \"similar objects\": [\"coaster\", \"yacht\"]}"}, {"object": "keg", "object_id": 602, "gpt3_output": "\n\n{\"type\": \"beacon\", \"description\": \"a light in the sky\", \"similar objects\": [\"keg\", \"keenah (ice cream)\", \"kelp\"]}"}, {"object": "kennel", "object_id": 603, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black and white stripes; has a long mane\", \"similar objects\": [\"horse\", \"giraffe\", \"elephant\"]}"}, {"object": "kettle", "object_id": 604, "gpt3_output": "\n\n{\"type\": \"pot\", \"description\": \"green, has a handle\", \"similar objects\": [\"carafe\", \"sink\", \"teapot\"]}"}, {"object": "key", "object_id": 605, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"key\", \"description\": \"round, black, has a handle\", \"similar objects\": [\"keyboard\", \"blu-screen\", \"tronque\"]"}, {"object": "keycard", "object_id": 606, "gpt3_output": "\n\n{\"type\": \"card\", \"description\": \"red; has a card on it\", \"similar objects\": [\"cardigan\", \"wallet\", \"keycard\"]"}, {"object": "kilt", "object_id": 607, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"Kilt\", \"quantity\": \"1\", \"similar objects\": [\"kilt\", \"shirt\"]}"}, {"object": "kimono", "object_id": 608, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"type_name\": \"vegetable\"},\n\n{\"type\": \"object\", \"name\": \"crab\", \"type_name\": \"crab\"},\n\n{\"type\": \"object\", \"name\": \"apple\", \"type_name\": \"apple\"},\n\n{\"type\": \"object\", \"name\": \"giraffe\", \"type_name\": \"giraffe\"},\n\n{\"type\": \"object\", \"name\": \"elephant\", \"type_name\": \"elephant\"},\n\n}"}, {"object": "kitchen_sink", "object_id": 609, "gpt3_output": "\n\n{\"type\": \"stream\", \"description\": \"x1\", \"x2\": \"x3\", \"x4\": \"x5\", \"x6\": \"x7\", \"x7\": \"x8\", \"x8\": \"x9\", \"x9\": \"x10\", \"x10\": \"x11\", \"x11\": \"x12\", \"x12\": \"x13\", \"x13\": \"x14\", \"x14\": \"x15\"}\n\nInput: sink, Output: \n\n{\"type\": \"stream\", \"description\": \"x1\", \""}, {"object": "kitchen_table", "object_id": 610, "gpt3_output": "\n\n{\"type\": \"table\", \"description\": \"black, with a white line at the center\", \"similar objects\": [\"cat\", \"coaster\", \"tray\", \"couch\"]"}, {"object": "kite", "object_id": 611, "gpt3_output": "\n\nThe object detection model should focus on finding objects with similar characteristics that are found other objects in the scene. The model should also be able to identify different types of objects, such as vegetables and animals."}, {"object": "kitten", "object_id": 612, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cat\", \"toucan\"]}"}, {"object": "kiwi_fruit", "object_id": 613, "gpt3_output": "\n\n{\"type\": \"fruit\", \"description\": \" Kiwi, green, firm\", \"similar objects\": [\"apple\", \"fruit\", \"grape\"]}"}, {"object": "knee_pad", "object_id": 614, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"red; has a bandage on the knee\", \"similar objects\": [\"knee pad\", \"bandage\", \"sock\", \"booties\", \"shoe\"]"}, {"object": "knife", "object_id": 615, "gpt3_output": "\n\n{\"type\": \" knife\", \"name\": \"Dirty Knee\" }\n\n{\"type\": \" knife\", \"name\": \"Dirty Knee\" }"}, {"object": "knitting_needle", "object_id": 616, "gpt3_output": "\n\n{\"type\": \"numeric\", \"position\": \"1\", \"description\": \"n/a\", \"type\": \"numeric\", \"vendor\": \"n/a\", \"age\": \"n/a\", \"stain\": \"n/a\", \"lack\": \"n/a\", \"stainest: \"n/a\", \"stainest: \"n/a\", \"stainest: \"n/a\", \"vendorname\": \"n/a\", \"vendorname: n/a\", \"vendorname: n/a\", \"vendorname:"}, {"object": "knob", "object_id": 617, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for signs of life is the model's ability to identify objects like woks and ambulances. This ability would include models that be created with and without handles, and models that are in multiple sizes."}, {"object": "knocker_(on_a_door)", "object_id": 618, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, smooth; has a small hole in the middle\", \"similar objects\": [\"zucchini\", \"carrot\", \"zucchini\"], \"similar objects\": [\"pan\", \"pot\", \"frying pan\", \"pan\", \"frying pan\", \"carrot\", \"zucchini\", \"pan\", \"zucchini\", \"vegetable\", \"vegetable\", \"carrot\", \"zucchini\", \"vegetable\", \"pan\", \"frying pan\", \"frying pan\", \"carrot\", \""}, {"object": "koala", "object_id": 619, "gpt3_output": "\n\n{\"type\": \" mammal \", \"description\": \"black and white, fur is long and long\", \"similar objects\": [\"alpacas\", \"cattle\", \"giraffe\"]}"}, {"object": "lab_coat", "object_id": 620, "gpt3_output": "\n\n{\"type\": \"clothing\", \"description\": \"black, white, red; has a collar\", \"similar objects\": [\"coat\", \"coat of arms\", \"bathrobe\"]}"}, {"object": "ladder", "object_id": 621, "gpt3_output": "\n\n{\"type\": \"crate\", \"description\": \"A simple ladder has a simple design and has a single rung, used for suspending goods at a craft store\", \"similar objects\": [\"door\", \"bridge\", \"latch\"]"}, {"object": "ladle", "object_id": 622, "gpt3_output": "\n\n{\"type\": \"dishwasher\", \"description\": \"round, has a spout\", \"similar objects\": [\"pansy\", \"grocery store\", \"coaster\"]"}, {"object": "ladybug", "object_id": 623, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"Ladybug\"},\n\n{\"type\": \"object\", \"name\": \"Ladybug\"},"}, {"object": "lamb_(animal)", "object_id": 624, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, red; has a long mane\", \"similar objects\": [\"fry\", \"chicken\", \"gazelle\"]}"}, {"object": "lamb-chop", "object_id": 625, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, red, or green, fur or hair, scale or motion-sensitive cells\", \"similar objects\": [\" lamb \", \"chop of lamb \", \"chop of chicken \"],"}, {"object": "lamp", "object_id": 626, "gpt3_output": "\n\nThe features that should be focus for an object detection model that smells zucchini should be the cylindrical shape, the smooth surface, and the green color. The model should be able to identify zucchini as a food item, but should not be able to identify the object itself."}, {"object": "lamppost", "object_id": 627, "gpt3_output": "\n\nThere are many different objects that can be detected by object detection models, depending on the input. This input includes objects like vegetables, animals, and tools. If you're looking for features that are specific to objects, you might want to focus on that type of object. If you're looking for features that are general, you might want to focus on features that are specific to that type of object."}, {"object": "lampshade", "object_id": 628, "gpt3_output": "\n\nThe feature of an object that should be focused on for object detection models is the object's object-of-interest (OI). This means that the model should be able to identify an object as being of interest based on its OI. This includes cylindrical objects, such as woks and ambulances, which typically have a round body and deep handle. These models would be interestable to a model because they have a high chance of being interested in the zucchini and producing a reaction in it."}, {"object": "lantern", "object_id": 629, "gpt3_output": "\n\n{\"type\": \"light tool\", \"description\": \"round; could be made of papers\", \"similar objects\": [\"lamp\", \"flashlight\", \"candle\"]"}, {"object": "lanyard", "object_id": 630, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"small, white, black, has a knot\"}, \"similar objects\": [\"ring\", \"cursor\", \"bunny earrings\", \"tongue\"]"}, {"object": "laptop_computer", "object_id": 631, "gpt3_output": "\n\n{\"type\": \"computer\", \"description\": \"black, with a red light\", \"similar objects\": [\"computer\", \"laptop\", \"tablet\"]}"}, {"object": "lasagna", "object_id": 632, "gpt3_output": "\n\n{\"type\": \"dessert\", \"description\": \"red; has a smooth surface\", \"similar objects\": [\"mango\", \"chocolate\", \"island\"]}"}, {"object": "latch", "object_id": 633, "gpt3_output": "\n\n{\"type\": \"mechanical device\", \"description\": \"round, has a latch\", \"similar objects\": [\"door\", \"latch\", \"washer\"]}"}, {"object": "lawn_mower", "object_id": 634, "gpt3_output": "\n\n{\"type\": \"tool\", \"description\": \"round, has a blade\", \"similar objects\": [\"mower\", \"chopper\", \"patio mower\"]"}, {"object": "leather", "object_id": 635, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"Leather\", \"description\": \"The material is black, it has a hard texture and it is a good material for bags and bags for children.\"}"}, {"object": "legging_(clothing)", "object_id": 636, "gpt3_output": "\n\n{\"type\": \"textbook\", \"description\": \"A Vegetable Gardener's Manual\", \"similar objects\": [\"green tea\"]}"}, {"object": "Lego", "object_id": 637, "gpt3_output": "\n\nThe input should be a model of a Lego set."}, {"object": "legume", "object_id": 638, "gpt3_output": "\n\nThere are many different plant and animal models that can be used for object detection. Object detection models can focus on one or more of these models."}, {"object": "lemon", "object_id": 639, "gpt3_output": "\n\n{\"type\": \"fruit\", \"description\": \"red, has a stem\", \"similar objects\": [\"lemon\", \"banana\", \"pear\"]}"}, {"object": "lemonade", "object_id": 640, "gpt3_output": "\n\n{\"type\": \"fruit\", \"description\": \"yellow, has a peel and bits of sugar\", \"similar objects\": [\"banana\", \"peach\"]}"}, {"object": "lettuce", "object_id": 641, "gpt3_output": "\n\nThe feature that should focus on for an input with a zucchini would be its type: zucchini. The input could also have similar objects, such as a cucumber, eggplant, and green bean."}, {"object": "license_plate", "object_id": 642, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for plates is the object's size. For example, an ambulance would be large if it was looking for plates, while a lightbulb would be large if it was looking for objects with lightening flashes."}, {"object": "life_buoy", "object_id": 643, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for water is its ability to find and respond to water-based objects. This object might be a water droplet, a water droplet's head, or a water droplet's body. The object detection model that is looking for other types of objects, such as fruits and vegetables, should focus on those objects."}, {"object": "life_jacket", "object_id": 644, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"x-shaped, has a line of plastic material on the front\", \"similar objects\": [\"life jacket\", \"latch\"]}"}, {"object": "lightbulb", "object_id": 645, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"lightbulb\", \"description\": \"round, green, at a angle towards the light\"}\n\nInput: light, Output: \n\n{\"type\": \"object\", \"name\": \"light\", \"description\": \"round, green, at a angle towards the light\"}"}, {"object": "lightning_rod", "object_id": 646, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"lightning rod\", \"type\": \"object\"}, {\"type\": \"object\", \"name\": \"lamp\", \"type\": \"object\"}, {\"type\": \"object\", \"name\": \"flashlight\", \"type\": \"object\"}"}, {"object": "lime", "object_id": 647, "gpt3_output": "\n\nThe feature that should focus on for an input with a lime is its color. This input should have features that can help you determine if the lime is a real fruit or not. You should also want to see if the lime has any roughness or smoothness to it."}, {"object": "limousine", "object_id": 648, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"black, red, yellow; could have a blue and red stripe\", \"similar objects\": [\"car\", \"taxi\", \"taxiway\", \"luxury car\"]}"}, {"object": "lion", "object_id": 649, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, or light-colored; has a lion's mane or hair, a lion's claws, or teeth\", \"similar objects\": [\"zebra\", \"giraffe\", \" elephant \", \" horse \", \" car\"]}"}, {"object": "lip_balm", "object_id": 650, "gpt3_output": "\n\nThere are many different object detection models that could be used for a zucchini. A model for this type of object could be the object detection model for vegetables. This model should focus on cylindrical objects with smooth stems, and similar objects that are could have rough stems. The model should also focus on lights and objects that have manes (happenings where the object has multiple colors)."}, {"object": "liquor", "object_id": 651, "gpt3_output": "\n\n{\"type\": \"liquor\", \"description\": \"red; has a sour taste\", \"similar objects\": [\"beer\", \"wine\", \"screwdriver\"]}"}, {"object": "lizard", "object_id": 652, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "log", "object_id": 653, "gpt3_output": "\n\nThe feature that should focus on for an input with a lot of change is the ability to detect different types of objects. For an input with few objects, like zucchini, object detection models should focus on finding simple objects, like cylindrical objects or objects with green or smooth stems."}, {"object": "lollipop", "object_id": 654, "gpt3_output": "\n\n{\"type\": \"toy\", \"description\": \"red, has a sugar coating\", \"similar objects\": [\"taco\", \"taco salad\", \"chocolate cake\"]}"}, {"object": "speaker_(stero_equipment)", "object_id": 655, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"small; has a sound effect\"}, \"similar objects\":"}, {"object": "loveseat", "object_id": 656, "gpt3_output": "\n\n{\"type\": \"seating\", \"description\": \"round, comfortable; could be in a corner\", \"similar objects\": [\"leather sofisticated seat\", \"coffee table\", \"coaster\"]"}, {"object": "machine_gun", "object_id": 657, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for evidence of an input is evidence of an input. This could be in the form of an input name, an input type, or even an input's own input type. In some cases, it might also be important to look for evidence of input activity. This can be in the form of input data such as input values or input models."}, {"object": "magazine", "object_id": 658, "gpt3_output": "\n\nThe objects in the input could be articles of clothing, such as a shirt or a dress. The objects in the group could be objects that make up a magazine, such as stories or images. or objects that make up a magazine, such as stories or images."}, {"object": "magnet", "object_id": 659, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for magnetism is the models ability to detect movement. This includes models that are designed to detect movement in objects, such as those used by police departments. In order to make sure the model is effective, the magnet should be able to detect movement on the object, as well as the model should have the ability to light up when detect movement."}, {"object": "mail_slot", "object_id": 660, "gpt3_output": "\n\n{\"type\": \"slot\", \"description\": \"red; with a small hole in the middle\", \"similar objects\": [\"slot machine\", \"slot\", \"slot machine\"], \"similar objects\": [\"slot machine\", \"slot\", \"slot machine\"], \"similar objects\": [\"slot machine\", \"slot\", \"slot machine\"], \"similar objects\": [\"slot machine\", \"slot\", \"slot machine\"], \"similar objects\": [\"slot machine\", \"slot\", \"slot machine\"], \"similar objects\": [\"slot machine\", \"slot\", \"slot machine\"], \"similar objects\": [\"slot machine\", \"slot\", \"slot machine\"], \""}, {"object": "mailbox_(at_home)", "object_id": 661, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"object\", \"description\": \"\"}"}, {"object": "mallard", "object_id": 662, "gpt3_output": "\n\n{\"type\": \"gazelle\", \"description\": \"light brown fur; could have black fur\", \"similar objects\": [\"gazelle\", \"chick\", \"toucan\"]}"}, {"object": "mallet", "object_id": 663, "gpt3_output": "\n\n{\"type\": \"all-purpose\", \"description\": \"bristly, could hit something with it\", \"similar objects\": [\"dagger\", \"harp\"]"}, {"object": "mammoth", "object_id": 664, "gpt3_output": "\n\n{\"type\": \"livestock\", \"description\": \"red; has a huge body; could have multiple calves\", \"similar objects\": [\"bison\", \" elk \", \" elk \", \"indigo \"],"}, {"object": "manatee", "object_id": 665, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, or light brown; has a long neck\", \"similar objects\": [\"cat\", \"toucan\", \"seagull\"]}"}, {"object": "mandarin_orange", "object_id": 666, "gpt3_output": "\n\n{\"type\": \"fruit\", \"description\": \"orange\", \"similar objects\": [\"mango\", \"grape\", \"apple\"]}"}, {"object": "manger", "object_id": 667, "gpt3_output": "\n\n{\"type\": \"person\", \"description\": \"black, white, or green; could have a head and body\", \"similar objects\": [\"cat\", \"dog\", \"horse\"]}"}, {"object": "manhole", "object_id": 668, "gpt3_output": "\n\nThere are many different objects that can be used as input for object detection models. Some examples include the following:\n\n-Vegetables\n-Fruits\n-Bacteria\n-Disease objects\n\nEach of these objects can be used to create a model that can detect whether a given object is a vegetable, a fruit, or a disease object. The model can be used to detect if the object is smooth, cylindrical, green, or rough. The model can also detect if the object has a stem and if it is sliced into round pieces or if it has green leaves."}, {"object": "map", "object_id": 669, "gpt3_output": "\n\nThe feature of an object that should focus on for object detection models looking for similar objects is its size. Size is a major factor when it comes to finding objects, and a small, small object will be difficult to find with other search tools. Other features that should be focus on for object detection models include its color, shape, or size."}, {"object": "marker", "object_id": 670, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for signs of life is the model's ability to identify other objects in the environment. Other features that should be considered for an object detection model that is looking for signs of life include the model's ability to identify objects as being related, such as an object that is being cooked on a stove, or an object that is being handled. The model should be able to identify whether or not each object is related to the one before it, and should be able to determine if each object is life-threatening."}, {"object": "martini", "object_id": 671, "gpt3_output": "\n\n{\"type\": \"cocktail\", \"description\": \"salt and pepper,\" \"similar objects\": [\"taco\", \"chicken\", \"nosegay\"]}"}, {"object": "mascot", "object_id": 672, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, smooth; has a green stem; could have rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "mashed_potato", "object_id": 673, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, smooth; could have rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"butterfly\", \"dip\", \"snowflake\"]}"}, {"object": "masher", "object_id": 674, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, smooth; could have rough stems; could be chopped into small pieces\", \"similar objects\": [\"zucchini\", \"butterfly\", \"toucan\"]}"}, {"object": "mask", "object_id": 675, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"mask\", \"type\": \"object\"}, {\"type\": \"object\", \"name\": \"mask\", \"type\": \"object\"}, {\"type\": \"object\", \"name\": \"mask\", \"type\": \"object\"}, {\"type\": \"object\", \"name\": \"mask\", \"type\": \"object\"}"}, {"object": "mast", "object_id": 676, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "mat_(gym_equipment)", "object_id": 677, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"mat\", \"flooring\", \"solar system\", \"watch\"]}"}, {"object": "matchbox", "object_id": 678, "gpt3_output": "\n\n{\"type\": \"item\", \"description\": \"red, with a matchstick in the middle\", \"similar objects\": [\"coaster\", \"troncone\", \" tear gas can\"]"}, {"object": "mattress", "object_id": 679, "gpt3_output": "\n\n{\"type\": \"bed\", \"description\": \"black, with a white cover\", \"similar objects\": [\"bed\", \"towel\", \"towel rack\"]}"}, {"object": "measuring_cup", "object_id": 680, "gpt3_output": "\n\n{\"type\": \"measures\", \"description\": \"staff with a handle\", \"similar objects\": [\"tape\", \"treadle\", \"sink\"]}"}, {"object": "measuring_stick", "object_id": 681, "gpt3_output": "\n\n{\"type\": \"measures\", \"description\": \"round, has a line for weight\", \"similar objects\": [\"inch\", \"centimeter\", \"millimeter\"]}"}, {"object": "meatball", "object_id": 682, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"beef\", \"chicken\", \"pork\"]}"}, {"object": "medicine", "object_id": 683, "gpt3_output": "\n\nThe model should focus on objects that have a smooth surface (such as a zucchini or vegetable), have green or brown stems (such as zebra or apple), and have similar objects in the input (such as a ambulance or Lantern)."}, {"object": "melon", "object_id": 684, "gpt3_output": "\n\n{\"type\": \"fruit\", \"description\": \"red, has a stem\", \"similar objects\": [\"apple\", \"banana\", \"pear\"]}"}, {"object": "microphone", "object_id": 685, "gpt3_output": "\n\nThere are many different objects that can be captured by an object detection model. These objects could include, but are not limited to, animals, vegetables, fruits, and so on."}, {"object": "microscope", "object_id": 686, "gpt3_output": "\n\nThe microscope should focus on objects with similar shapes and sizes, regardless of their color. The microscope should also be able to measure objects accurately, regardless of their size."}, {"object": "microwave_oven", "object_id": 687, "gpt3_output": "\n\n{\"type\": \"implement\", \"description\": \"round, has a bezel for food; could be used for baking or cooking\", \"similar objects\": [\"dishwasher\", \"fridge\", \"Refrigerator\"]"}, {"object": "milestone", "object_id": 688, "gpt3_output": "\n\n{\"type\": \"infrastructure\", \"description\": \"round, has a handle, has a beveled edge\", \"similar objects\": [\"rail\", \"bridge\", \"tunnel\"]}"}, {"object": "milk", "object_id": 689, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "milk_can", "object_id": 690, "gpt3_output": "\n\n{\"type\": \"ulcer\", \"description\": \"a small, round, black object\", \"similar objects\": [\"pudding\", \"ulcer\", \"gumbo\"]}"}, {"object": "milkshake", "object_id": 691, "gpt3_output": "\n\n{\"type\": \"drink\", \"description\": \"white, bubbly water with a sour smell\", \"similar objects\": [\"milkshake\", \"shower\", \"shampoo\"]}"}, {"object": "minivan", "object_id": 692, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"red; has a shining side mirror; could have a spoiler\", \"similar objects\": [\"car\", \"truck\", \"SUV\"]"}, {"object": "mint_candy", "object_id": 693, "gpt3_output": "\n\nThe feature that should focus on for an input with a candy color is the model's ability to detect candy. The model should be able to identify candy-colored objects as well as other colors."}, {"object": "mirror", "object_id": 694, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"type_name\": \"vegetable\"},\n\n{\"type\": \"object\", \"name\": \"crab\", \"type_name\": \"crusty_crab\"},\n\n{\"type\": \"object\", \"name\": \"apple\", \"type_name\": \"fruit\"},\n\n{\"type\": \"object\", \"name\": \"giraffe\", \"type_name\": \"elephant\"},\n\n}"}, {"object": "mitten", "object_id": 695, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"small; has a hole in the center\", \"similar objects\": [\"pouch\", \"mug\"]}"}, {"object": "mixer_(kitchen_tool)", "object_id": 696, "gpt3_output": "\n\n{\"type\": \"ingredient\", \"description\": \"ingredient\", \"inputs\": [\"frozen fruit\", \"frozen vegetables\", \"frozen meat\", \"frozen milk\", \"frozen cream\", \"frozen yogurt\", \"frozen ice cream\"]}"}, {"object": "money", "object_id": 697, "gpt3_output": "\n\nThere are many different objects that can be used with money, including coins, pieces of paper, and lights."}, {"object": "monitor_(computer_equipment) computer_monitor", "object_id": 698, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for evidence of life is its ability to see objects in its surroundings. object detection models should be able to identify objects that have been in the same situation as you, such as a zucchini and a tomato. They should also be able to identify objects that are different in shape or color, such as a ambulance and a monitor."}, {"object": "monkey", "object_id": 699, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, or green; could have a tail\", \"similar objects\": [\"toucan\", \"seagull\", \"whale\"]}"}, {"object": "motor", "object_id": 700, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"red; has atering system; could have multiple engines\", \"similar objects\": [\"car\", \"truck\", \"motor vehicle\"]}"}, {"object": "motor_scooter", "object_id": 701, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for a zucchini is its size. This model should be able to find objects that are smaller than itself. Additionally, the model should be able to find models that are the same size, such as a scooter."}, {"object": "motor_vehicle", "object_id": 702, "gpt3_output": "\n\nThe input should be a vehicle."}, {"object": "motorcycle", "object_id": 703, "gpt3_output": "\n\nThe object detection model should focus on finding objects with similar characteristics. For example, an object that is similar to a motorcycle would be found with objects that are similar to motorcycles."}, {"object": "mound_(baseball)", "object_id": 704, "gpt3_output": "\n\nThe object detection model should focus on finding objects with similar characteristics that are located at or near the base of the mound. The model should also be able to identify objects that are different types of objects, such as animals and tools."}, {"object": "mouse_(computer_equipment)", "object_id": 705, "gpt3_output": "\n\n{\"type\": \"computer\", \"description\": \"round, has a on/off switch\", \"similar objects\": [\"keyboard\", \"pointer\", \"touch screen\"]}"}, {"object": "mousepad", "object_id": 706, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"mousepad\"}, {\"type\": \"object\", \"name\": \"mouse\"}, {\"type\": \"object\", \"name\": \"keyboard\"}, {\"type\": \"object\", \"name\": \"trued\", \"date\": \"2018-10-14T19:00:00\", \"similar objects\": [\"xbox\", \"foggy\", \"snowy\", \"reptile\"]}"}, {"object": "muffin", "object_id": 707, "gpt3_output": "\n\n{\"type\": \"cake\", \"description\": \"round, has a hole in the middle\", \"similar objects\": [\"foam plane\", \"butterfly\", \"muffin\",\"]}"}, {"object": "mug", "object_id": 708, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"Mug\", \"description\": \"\n\nThis mug is for drinking from. It is big and has a lot of color."}, {"object": "mushroom", "object_id": 709, "gpt3_output": "\n\n{\"type\": \"mushroom\", \"name\": \"albacore\", \"shoots\": \"ulles\", \"format\": \"lilac\", \"description\": \"\n\nA Mushroom is a very small, white,bumpy object that lives in water. It has a long mane of black hair and green eyes. The stem is short and red."}, {"object": "music_stool", "object_id": 710, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"Music Stool\", \"description\": \"A stool with a lighted surface that plays music\", \"similar objects\": [\"lamp\", \"flashlight\", \"candle\"]"}, {"object": "musical_instrument", "object_id": 711, "gpt3_output": "\n\nInput: flute, Output:\n\n{\"type\": \"instrument\", \"description\": \"flute\", \"similar objects\": [\"guitar\", \"banjo\", \"fife\"]}"}, {"object": "nailfile", "object_id": 712, "gpt3_output": "\n\n{\"type\": \"file\", \"name\": \"Nailfile\", \"size\": \"\", \"similar objects\": [\"file\", \"brick\", \"fiberglass \"\", \"brick\"]"}, {"object": "napkin", "object_id": 713, "gpt3_output": "\n\n{\"type\": \"appetizer\", \"description\": \"1-2 tablespoons of oil or butter is all that's needed\", \"similar objects\": [\"taco\", \"taco shell\", \"taco sauce\"]"}, {"object": "neckerchief", "object_id": 714, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"neckerchief\", \"type\": \"object\"}, {\"type\": \"object\", \"name\": \"neckerchief\", \"type\": \"object\"},"}, {"object": "necklace", "object_id": 715, "gpt3_output": "\n\n{\"type\": \" necklace\", \"description\": \"green; has a small hole in the center\", \"similar objects\": [\"bronze necklace\", \"silver necklace\"]}"}, {"object": "necktie", "object_id": 716, "gpt3_output": "\n\n{\"type\": \"collar\", \"description\": \"thin; has a knot in the neck\", \"similar objects\": [\"necklace\", \" scarf \", \" tie \"], }"}, {"object": "needle", "object_id": 717, "gpt3_output": "\n\n{\"type\": \"nail\", \"description\": \"black, has a sharp point\", \"similar objects\": [\"nail\", \"nailgun\", \"tinder box\"]"}, {"object": "nest", "object_id": 718, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, red, green, blue\", \"similar objects\": [\"chicken\", \"egg\", \"nose\", \"banana\"]}"}, {"object": "newspaper", "object_id": 719, "gpt3_output": "\n\nThe objects in the input could be objects that are all objects in the input, or could focus on specific types of objects in the input. The model should be able to identify and track the progress of an object in the input, so that it can start cooking or lighting up."}, {"object": "newsstand", "object_id": 720, "gpt3_output": "\n\nThe object detection model should focus on objects that have either smooth stems or have smooth bumps on their stem. The model should also be able to identify similar objects, such as a zebra or an ambulance."}, {"object": "nightshirt", "object_id": 721, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"nightshirt\", \"id\": \"\", \"has\": [\"type\"]}"}, {"object": "nosebag_(for_animals)", "object_id": 722, "gpt3_output": "\n\n{\"type\": \"item\", \"description\": \"black, with a white bag inside\", \"similar objects\": [\"nosebag\", \"nosecone\", \"nose\", \"flask\"]}"}, {"object": "noseband_(for_animals)", "object_id": 723, "gpt3_output": "\n\n{\"type\": \"noseband\", \"description\": \"\", \"similar objects\": [\"nose\", \" Nose\", \" Nose band \"\", \" similar objects \"\", \" lips \"\", \" lips \"\", \" lips \"\", \" lips \"\", \" lips \"\", \" lips \"\", \" lips \"\", \" lips \"\", \" lips \"\", \" lips \"\", \" lips \"\", \" lips \"\", \" lips \"\", \" lips \"\", \" lips \"\", \" lips \"\", \" lips \"\", \" lips \"\", \" lips \"\", \" lips \"\", \" lips \"\", \" lips \"\", \" lips \"\","}, {"object": "notebook", "object_id": 724, "gpt3_output": "\n\n{\"type\": \"book\", \"description\": \"black, smooth, has a spine\", \"similar objects\": [\"envelope\", \"notepad\", \"notebook\"]"}, {"object": "notepad", "object_id": 725, "gpt3_output": "\n\nThere are many different features that object detection models could focus on. One example is that of items that have similar shapes or objects that have the same shape. Another example is that of items that have the same size or weight. Finally, object detection models could focus on specific types of items, such as those that are cooked or burning."}, {"object": "nut", "object_id": 726, "gpt3_output": "\n\n{\"type\": \"nut\", \"description\": \"black, smooth\", \"similar objects\": [\"salt and sugar\", \"salt and pepper\", \"onion\"]}"}, {"object": "nutcracker", "object_id": 727, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for nuts is the object's body. This will include everything from the inside out to how it fits into the world."}, {"object": "oar", "object_id": 728, "gpt3_output": "\n\n{\"type\": \"vessel\", \"description\": \"round, has a mouth\", \"similar objects\": [\"fishing net\", \"fishing gear\", \"ripper\"]"}, {"object": "octopus_(food)", "object_id": 729, "gpt3_output": "\n\n{\"type\": \"insect\", \"description\": \"black, white, small; has a proboscis and a proboscidea\", \"similar objects\": [\"octopus\", \"puma\", \"urk\"]}"}, {"object": "octopus_(animal)", "object_id": 730, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"octopus\", \"nose cone\", \"octopus book\"]}"}, {"object": "oil_lamp", "object_id": 731, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for signs of life is the object's size. Other features that might be important for a model to focus on include the object's shape (cyilless, handle, smooth), the object's color (black or white), the object's texture (gouged or smooth), and the object's movement (dancing or spasmodic)."}, {"object": "olive_oil", "object_id": 732, "gpt3_output": "\n\n{\"type\": \"chemical\", \"description\": \"grape seed oil\", \"similar objects\": [\"salt\"]}"}, {"object": "omelet", "object_id": 733, "gpt3_output": "\n\n{\"type\": \"dish\", \"description\": \"onion, bacon, ham\", \"similar objects\": [\"parmesan cheese\", \"butterfly\", \"mutton\"]}"}, {"object": "onion", "object_id": 734, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, or light-colored; has a head\", \"similar objects\": [\"pig\", \"goat\", \"cat\"]}"}, {"object": "orange_(fruit)", "object_id": 735, "gpt3_output": "\n\n{\"type\": \"fruit\", \"description\": \"orange\", \"similar objects\": [\"apple\", \"banana\", \"pear\"]}"}, {"object": "orange_juice", "object_id": 736, "gpt3_output": "\n\n{\"type\": \"fruit\", \"description\": \"light orange\", \"similar objects\": [\"fruit\", \"fruit salad\", \"fruit juice\"]}"}, {"object": "ostrich", "object_id": 737, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black and white, has a long neck\", \"similar objects\": [\"giraffe\", \"otter\", \"coaster\"]}"}, {"object": "ottoman", "object_id": 738, "gpt3_output": "\n\n{\"type\": \"obj\", \"description\": \"a piece of furniture; a surface to hold objects; a surface for holding objects and for displaying them\", \"similar objects\": [\"coaster\", \"desk\", \"trucker bar\", \"bookcase\"]}"}, {"object": "oven", "object_id": 739, "gpt3_output": "\n\n{\"type\": \"implement\", \"description\": \"should bake goods such as bread, oven-baked goods, and such\", \"similar objects\": [\"pizza\", \"chocolate cake\", \"dessert cake\"]}"}, {"object": "overalls_(clothing)", "object_id": 740, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \" overalls \", \"description\": \"\", \"similar objects\": [\"pants\", \"shirt\", \"hat\"]}"}, {"object": "owl", "object_id": 741, "gpt3_output": "\n\n{\"type\": \"wing\", \"description\": \"dark, with a beak\", \"similar objects\": [\"clam\", \"gazelle\", \"albatross\"]}"}, {"object": "packet", "object_id": 742, "gpt3_output": "\n\n{\"type\": \"packet\", \"description\": \"red; has aillon or white spot on one end\", \"similar objects\": [\"spyderm\", \"virus\", \"stain\"]}"}, {"object": "inkpad", "object_id": 743, "gpt3_output": "\n\n{\"type\": \"application\", \"name\": \"imprint\", \"description\": \"\n\nThe object detection model should focus on identifying objects that have the same name as the one that is being printed. For example, the imprint model should be able to identify the object as \"imprint\" because it has the same name as the one that is being printed."}, {"object": "pad", "object_id": 744, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"type_name\": \"vegetable\"},\n\n{\"type\": \"object\", \"name\": \"crab\", \"type_name\": \"crusty_crab\"},\n\n{\"type\": \"object\", \"name\": \"apple\", \"type_name\": \"fruit\"},\n\n{\"type\": \"object\", \"name\": \"giraffe\", \"type_name\": \"elephant\"},\n\n}"}, {"object": "paddle", "object_id": 745, "gpt3_output": "\n\n{\"type\": \"boat\", \"description\": \"black, with a white/black hull\", \"similar objects\": [\"house\", \"seawater\", \"seaweed\"]}"}, {"object": "padlock", "object_id": 746, "gpt3_output": "\n\n{\"type\": \"key\", \"description\": \"a keyhole\", \"similar objects\": [\"key\", \"ring\"]"}, {"object": "paintbrush", "object_id": 747, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is detecting objects in the input is the ability to have objects have different colors. An object detection model that is looking for objects in the input that have different colors will be more able to identify them and to provide a report on their activity."}, {"object": "painting", "object_id": 748, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for paintings is the type of the object. For example, an ambulance would focus on the type of the object: \"round; has a glaring siren; could with a stretcher\"."}, {"object": "pajamas", "object_id": 749, "gpt3_output": "\n\n{\"type\": \"pajama\", \"description\": \"light blue and white, with a low back and sides\", \"similar objects\": [\"pajama\", \"nightshirt\", \"nightstand\", \"tablet\"]}"}, {"object": "palette", "object_id": 750, "gpt3_output": "\n\n{\"type\": \"set\", \"name\": \"dos\", \"description\": \"pale, light blue, several light blue shades\", \"similar objects\": [\"toilet\", \"cabin\", \" kitchen\"]}"}, {"object": "pan_(for_cooking)", "object_id": 751, "gpt3_output": "\n\n{\"type\": \"dish\", \"description\": \"etitive,\" \"ingredients\": [\"pork\", \"chicken\"]}"}, {"object": "pan_(metal_container)", "object_id": 752, "gpt3_output": "\n\n{\"type\": \"pan\", \"name\": \"dishpan\", \"size\": \"small\", \"handle\": \"cucumber\", \"sliced\": \"eggplant\", \"color\": \"green\", \"salt\": \"sliced\", \"oon\": \"cucumber\", \"oon\": \"green bean\", \"oon\": \"zebra\", \"oon\": \"banana\", \"oon\": \"pear\", \"oon\": \"orange\", \"oon\": \"dishpan\", \"oon\": \"frying pan\", \"oon\": \"pot\", \"oon\": \"frying pan\", \"oon"}, {"object": "pancake", "object_id": 753, "gpt3_output": "\n\n{\"type\": \"cake\", \"description\": \"white, with a white layer of batter on top\", \"similar objects\": [\"pan\", \"dessert\", \"muffin\",\"]}"}, {"object": "pantyhose", "object_id": 754, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"pantyhose\", \"description\": \"A pair of pantyhose.\n\" }\n\nInput: soap, Output: \n\n{\"type\": \"object\", \"name\": \"soap\", \"description\": \"A soapy dish."}, {"object": "papaya", "object_id": 755, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cyan, has a smooth surface\", \"similar objects\": [\"fruit\", \"vegetable\", \"salad\"]}"}, {"object": "paper_plate", "object_id": 756, "gpt3_output": "\n\nThe feature of the plate that should be focus for object detection models is the fact that it is typically made of paper. This plate could be used for example to detect objects that have paper-like properties."}, {"object": "paper_towel", "object_id": 757, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"paper towel\", \"description\": \"red; has a handle\", \"similar objects\": [\"koozie\", \"towel\", \"sink\"]}"}, {"object": "paperback_book", "object_id": 758, "gpt3_output": "\n\n{\"type\": \"book\", \"description\": \"red; has a high-quality cover\", \"similar objects\": [\"patience\", \"envelope\", \"envelope\"]"}, {"object": "paperweight", "object_id": 759, "gpt3_output": "\n\nThe feature that should focus on for an object detection model thats looking for patterns in an input such as zucchini would be the presence or absence of patterns in the input."}, {"object": "parachute", "object_id": 760, "gpt3_output": "\n\n{\"type\": \" parachute \", \"description\": \"A type of parachute that is used to help people fall out of airplanes\", \"type \", \"url \", \"image \", \"alt ,\"\"alt \"\", \"alt \"\", \"alt \"\", \"alt \"\", \"alt \"\", \"alt \"\", \"alt \"\", \"alt \"\", \"alt \"\", \"alt \"\", \"alt \"\", \"alt \"\", \"alt \"\", \"alt \"\", \"alt \"\", \"alt \"\", \"alt \"\", \"alt \"\", \"alt \"\", \"alt \"\", \"alt \"\", \"alt \"\", \""}, {"object": "parakeet", "object_id": 761, "gpt3_output": "\n\n{\"type\": \"insect\", \"description\": \"no description provided\"}, {\"type\": \"animal\", \"description\": \"black and white, has a long mane\", \"similar objects\": [\"toucan\", \"seagull\", \"giraffe\"]"}, {"object": "parasail_(sports)", "object_id": 762, "gpt3_output": "\n\n{\"type\": \"sports\", \"description\": \" Acts like a parachutist and allows for free fall . Acts as a tool for measuring distances and predicting wind speed \", \"similar objects\": [\"sailing boat\", \"sky box\"]}"}, {"object": "parasol", "object_id": 763, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves \"\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "parchment", "object_id": 764, "gpt3_output": "\n\nThe input should include a list of objects that are similar to the object being detected. For example, the zucchini might be a vegetable, while the zebra might be a animal. The input should also include a list of objects that are different from the object being detected. For example, the eggplant might be a fruit, while the green bean might be a vegetable."}, {"object": "parka", "object_id": 765, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"black, with a small hole in the back\", \"similar objects\": [\"sunglasses\", \"hat\"]}"}, {"object": "parking_meter", "object_id": 766, "gpt3_output": "\n\nThere are many different features an object detection model could focus on. An object detection model that focuses on the features of an input that is a \"vegetable\" will be more successful in detecting vegetables. An object detection model that focuses on the features of an input that is a \"vegetable\" will be more successful in detecting a veggie."}, {"object": "parrot", "object_id": 767, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, or green; could have a beak and a beak-like structure\", \"similar objects\": [\"parrot\", \"clam\", \"gazelle\"]}"}, {"object": "passenger_car_(part_of_a_train)", "object_id": 768, "gpt3_output": "\n\nThe input should be a specific object, such as a part of a train, that is used in the story. The output should be a story about a different object."}, {"object": "passenger_ship", "object_id": 769, "gpt3_output": "\n\nThe input should be a vehicle."}, {"object": "passport", "object_id": 770, "gpt3_output": "\n\n{\"type\": \"passport\", \"image\": \"image\", \"status\": \"active\"}, {\"type\": \"passport\", \"image\": \"image\", \"status\": \"inactive\"},"}, {"object": "pastry", "object_id": 771, "gpt3_output": "\n\n{\"type\": \"cake\", \"description\": \"white, with a red and white sugar coating\", \"similar objects\": [\"cake\", \"chocolate\", \"fruitcake\"]}"}, {"object": "patty_(food)", "object_id": 772, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"patty\", \"chicken\", \"egg\"]}"}, {"object": "pea_(food)", "object_id": 773, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"pea\", \"zucchini\", \"zucchini\"], \"similar objects\": [\"garden variety\", \"honeydew\", \"honeydew mould\"]}"}, {"object": "peach", "object_id": 774, "gpt3_output": "\n\n{\"type\": \"fruit\", \"description\": \"red, has a stem\", \"similar objects\": [\"apple\", \"banana\", \"pear\"]}"}, {"object": "peanut_butter", "object_id": 775, "gpt3_output": "\n\n{\"type\": \"dessert\", \"description\": \"sugar, butter, eggs\", \"similar objects\": [\"tahini\", \" membranee\", \"chocolate\"]}"}, {"object": "pear", "object_id": 776, "gpt3_output": "\n\n{\"type\": \"fruit\", \"description\": \"red, round, has a stem\", \"similar objects\": [\"orange\", \"banana\", \"pear\"]}"}, {"object": "peeler_(tool_for_fruit_and_vegetables)", "object_id": 777, "gpt3_output": "\n\n{\"type\": \"tool\", \"description\": \"removal of skin, flesh, and seeds\", \"similar objects\": [\"pulley\", \"sieve\", \"dishwasher\"]}"}, {"object": "wooden_leg", "object_id": 778, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"wooden leg\", \"description\": \"a wooden leg\""}, {"object": "pegboard", "object_id": 779, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"peach\", \"description\": \"red; has a hole in the center\", \"similar objects\": [\"peach\", \"gravy\", \"cake\"]}"}, {"object": "pelican", "object_id": 780, "gpt3_output": "\n\n{\"type\": \"bird\", \"description\": \"black, white, thin; has a neck\", \"similar objects\": [\"clam\", \"seaweed\", \"gazelle\"]}"}, {"object": "pen", "object_id": 781, "gpt3_output": "\n\nThe feature that should focus on for an input with a zucchini would be its type: zucchini, while the feature that should focus on for an input with a red wok would be its description: \"round; has a shining siren\"."}, {"object": "pencil", "object_id": 782, "gpt3_output": "\n\nThe input should be a specific, known object. The output should be an object that is similar to the input."}, {"object": "pencil_box", "object_id": 783, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"Zucchini\", \"description\": \"The zucchini is a vegetable.\"}\n\n{\"type\": \"object\", \"name\": \"Carrot\", \"description\": \"The carrot is a fruit.\"}\n\n{\"type\": \"object\", \"name\": \"Giraffe\", \"description\": \"The giraffe is a animal.\"}"}, {"object": "pencil_sharpener", "object_id": 784, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"a pencil sharpener; a pencil; a pencil sharpener\"}"}, {"object": "pendulum", "object_id": 785, "gpt3_output": "\n\nThe ability to detect objects in data that way will help researchers determine whether objects in the data are representative of objects in real life. By focusing on objects that are common to all types of objects, a model could be designed that can identify them."}, {"object": "penguin", "object_id": 786, "gpt3_output": "\n\n{\"type\": \" mammal \", \"description\": \"black and white, has a long mane\", \"similar objects\": [\"penguin\", \"seagull\"]}"}, {"object": "pennant", "object_id": 787, "gpt3_output": "\n\nThe feature of an object that should focus on for object detection models that are looking for a particular input: objects with a Pennant should be more focused on when looking for objects with similar characteristics."}, {"object": "penny_(coin)", "object_id": 788, "gpt3_output": "\n\n{\"type\": \"coin\", \"price\": 1, \"badge\": \"coined\", \"description\": \"penny\", \"variant\": \"coined\"}"}, {"object": "pepper", "object_id": 789, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for food is its size. Other features that might be important for an object are its color, weight, or shape."}, {"object": "pepper_mill", "object_id": 790, "gpt3_output": "\n\n{\"type\": \"ingredient\", \"description\": \"a pepper mill is a device used to grate and/or ground pepper\", \"similar objects\": [\"onion\", \"chicken\", \"drummer boy\", \"cat\"]}"}, {"object": "perfume", "object_id": 791, "gpt3_output": "\n\nThe type of scent an object can have is determined by the object's features. Object detectors should focus on features of objects that are similar to features of themselves. For example, an object's features should be those that are common to objects like cars, lights, and plants."}, {"object": "persimmon", "object_id": 792, "gpt3_output": "\n\n{\"type\": \"herb\", \"description\": \"red; has a stem and leaves\", \"similar objects\": [\"grape\", \"apple\", \"leek\"]}"}, {"object": "person", "object_id": 793, "gpt3_output": "\n\n{\"type\": \"person\", \"description\": \"black, white, red eyes\", \"similar objects\": [\"black cat\", \"white cat\"]}"}, {"object": "pet", "object_id": 794, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "pew_(church_bench)", "object_id": 795, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for evidence of life is the presence of a feature (or features) in the input that has the same appearance but different function. For example, the pew (church bench) in the input could be used for evidence of life because it is a place where people could sit and where religious services could be held. The round shape of the pew could help it to be used as an object detection model, because it can be thought of as a place with similar features that is not only round but also has a deep end and a handle."}, {"object": "phonebook", "object_id": 796, "gpt3_output": "\n\nThere are many different objects that can be looked for in a model that has the word \"object\" in its title. These models would focus on objects that have either round body parts (like a wok) or deep parts (like an ambulance). They would also look for models that have a siren, light, or phonebook that can be held up to the light to show that it is an ambulance."}, {"object": "phonograph_record", "object_id": 797, "gpt3_output": "\n\nThe input should have objects that are either recordable objects, or objects that are that are used in the production of records."}, {"object": "piano", "object_id": 798, "gpt3_output": "\n\n{\"type\": \"piano\", \"description\": \"smooth, has a bowl at the bottom\", \"similar objects\": [\"guitar\", \"bassoon\"]}"}, {"object": "pickle", "object_id": 799, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "pickup_truck", "object_id": 800, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"red; has a red top and red bottom; is fitted with stones and obstacles\", \"similar objects\": [\"car\", \"truck\", \"tractor\", \"island\"]}"}, {"object": "pie", "object_id": 801, "gpt3_output": "\n\n{\"type\": \"dessert\", \"description\": \"red; has a crusty crust; can be pieced together\", \"similar objects\": [\"mango\", \"chocolate\", \"fruitcake\"]}"}, {"object": "pigeon", "object_id": 802, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"pigeon\", \"gazelle\", \" elephant\"]}"}, {"object": "piggy_bank", "object_id": 803, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "pillow", "object_id": 804, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \" pillow \", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves \"\"}, \"similar objects\": [\"apple\", \"banana\", \"pear\"]"}, {"object": "pin_(non_jewelry)", "object_id": 805, "gpt3_output": "\n\nThere are many different types of objects that can be detected by object detection models. Some objects that are typically used in experiments include: vegetables, fruits, animals, and tools."}, {"object": "pineapple", "object_id": 806, "gpt3_output": "\n\n{\"type\": \"fruit\", \"description\": \"red, has a stem\", \"similar objects\": [\"apple\", \"banana\", \"pear\"]}"}, {"object": "pinecone", "object_id": 807, "gpt3_output": "\n\n{\"type\": \"nut\", \"description\": \"red; has a small hole in top\", \"similar objects\": [\"grape\", \"seaweed\", \"baked potato\"]}"}, {"object": "ping-pong_ball", "object_id": 808, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is ping-ponging between a vegetable and animal input is the size of the object. This will include size, shape, and color. The object's size should be able to handle the force of the game, and should be small enough that it can't cause any damage."}, {"object": "pinwheel", "object_id": 809, "gpt3_output": "\n\nThe ability to detect and track different types of objects in an environment can help drivers in different ways. For example, an ambulance could be able to see better in the dark, while a pinwheel could be more efficient in providing light in the dark."}, {"object": "tobacco_pipe", "object_id": 810, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for cigarettes is the object's color. Other features that could be used for an object detection model include its size, shape, and color."}, {"object": "pipe", "object_id": 811, "gpt3_output": "\n\n{\"type\": \"pipe\", \"description\": \"clear, has a-\", \"similar objects\": [\"soup pot\", \"soup\", \"catcher\"]}"}, {"object": "pistol", "object_id": 812, "gpt3_output": "\n\nThe objects that should be focus of an object detection model for a given input are those that have a smooth surface (such as zucchini, vegetables, animals), round body (such as a wok, cooker, or ambulance), deep body (such as a pistol or Lantern), or with a handle (such as a pistol or lantern)."}, {"object": "pita_(bread)", "object_id": 813, "gpt3_output": "\n\n{\"type\": \"dish\", \"description\": \"1. What type of zucchini?\n2. What is the description of the zucchini?\n3. What is the size of the zucchini?\n4. What is the color of the zucchini?\n5. What is the shape of the zucchini?"}, {"object": "pitcher_(vessel_for_liquid)", "object_id": 814, "gpt3_output": "\n\n{\"type\": \"vase\", \"description\": \"light green; has a small hole in the top\", \"similar objects\": [\"coaster\", \"coaster system\"]}"}, {"object": "pitchfork", "object_id": 815, "gpt3_output": "\n\n{\"type\": \"weapon\", \"description\": \"black, with a sharp point\", \"similar objects\": [\"fork\", \"pitchfork\", \" Baton \", \"sewer\"]}"}, {"object": "pizza", "object_id": 816, "gpt3_output": "\n\n{\"type\": \"food\", \"description\": \"red; has a hole in the center\", \"similar objects\": [\"pizza\", \"chicken\", \"gravy\"]}"}, {"object": "place_mat", "object_id": 817, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "plate", "object_id": 818, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, smooth; has a rough stem; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"beef bowl\", \"dishcloth\", \"coaster\"]}"}, {"object": "platter", "object_id": 819, "gpt3_output": "\n\n{\"type\": \"dish\", \"description\": \"black, white, rice and beans; could be rice and beans; could have a lot of rice; could be a platter of food}\""}, {"object": "playpen", "object_id": 820, "gpt3_output": "\n\n{\"type\": \"playpen\", \"description\": \"rodent-free; large enough to fit a large child\", \"similar objects\": [\"coaster\", \"esky\", \"playpen\", \"ottoman\"]}"}, {"object": "pliers", "object_id": 821, "gpt3_output": "\n\n{\"type\": \"tool\", \"description\": \"long, sharp, has a handle\", \"similar objects\": [\"pump\", \"pistol\", \"cise\", \"dagger\"]}"}, {"object": "plow_(farm_equipment)", "object_id": 822, "gpt3_output": "\n\nThe feature that should focus on for an input with a lot of change is features that could be used to get food for the farm. This could include things like machines that turn a key into and out from the farm, a plow, or a machine that pulls a wagon."}, {"object": "plume", "object_id": 823, "gpt3_output": "\n\nThe plume feature is important for objects that may have a lot of detail, such as a smoke or gas pipe."}, {"object": "pocket_watch", "object_id": 824, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for danger in an input such as zucchini is the model's knowledge of other objects in the world. These objects could be other vegetables, other animals, or even other pocket watches. The model should be able to identify them and help them protect their loved ones."}, {"object": "pocketknife", "object_id": 825, "gpt3_output": "\n\nThere are many different features an object detection model could focus on, such as detecting objects of different sizes, detecting shapes, and detecting the presence of specific objects."}, {"object": "poker_(fire_stirring_tool)", "object_id": 826, "gpt3_output": "\n\n{\"type\": \"tool\", \"description\": \"round, has a handle\", \"similar objects\": [\"dishwasher\", \"sink\", \"barrel\"]"}, {"object": "pole", "object_id": 827, "gpt3_output": "\n\n{\"type\": \"ingredient\", \"description\": \"\", \"type\": \"result\", \"result\": {\"type\": \"vegetable\", \"name\": \"zucchini\"}, \"type\": \"output\", \"description\": \"\", \"type\": \"vegetable\", \"name\": \"crushed\"}"}, {"object": "polo_shirt", "object_id": 828, "gpt3_output": "\n\n{\"type\": \"item\", \"description\": \"red; has a fabric fabricant\", \"similar objects\": [\"t-shirt\", \"shirt\"]}"}, {"object": "poncho", "object_id": 829, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"type_name\": \"vegetable\"},\n\n{\"type\": \"object\", \"name\": \"crab\", \"type_name\": \"crab\"},\n\n{\"type\": \"object\", \"name\": \"apple\", \"type_name\": \"apple\"},\n\n{\"type\": \"object\", \"name\": \"giraffe\", \"type_name\": \"giraffe\"},\n\n{\"type\": \"object\", \"name\": \"elephant\", \"type_name\": \"elephant\"},\n\n}"}, {"object": "pony", "object_id": 830, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black and white stripes; has a long mane\", \"similar objects\": [\"horse\", \"giraffe\", \"elephant\"]}"}, {"object": "pool_table", "object_id": 831, "gpt3_output": "\n\n{\"type\": \"table\", \"description\": \"black, with a white line at the center, for water to fall through\", \"similar objects\": [\"pool\", \"lid\", \"barrier\"]}"}, {"object": "pop_(soda)", "object_id": 832, "gpt3_output": "\n\n{\"type\": \"ingredient\", \"description\": \"soda\", \"vibration\": \"ingredient\", \"similar objects\": [\"soda\", \"pop\"]}"}, {"object": "postbox_(public)", "object_id": 833, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"Postbox\", \"type\": \"object\", \"description\": \"\n\n\n\nThe Postbox object is a simple object, meaning that it has no features that are not also in the other objects in the input. This object should focus on objects with features, such as description and type."}, {"object": "postcard", "object_id": 834, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for resemblances between two objects is the postcard. With similar objects, like a zebra and a postcard, postcards could be used for research or as advertising."}, {"object": "poster", "object_id": 835, "gpt3_output": "\n\nThe object detection model should focus on finding objects with similar characteristics. For example, an object with a round body and a round head would be considered a vegetable. If the object had rough stems, it would be considered a animal."}, {"object": "pot", "object_id": 836, "gpt3_output": "\n\n{\"type\": \"pot\", \"description\": \"green, has a handle\", \"similar objects\": [\"keg\", \"cicle\", \"casserole\"]}"}, {"object": "flowerpot", "object_id": 837, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"gazelle\", \"gazelle\", \"kangaroo\"]}"}, {"object": "potato", "object_id": 838, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "potholder", "object_id": 839, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"potholder\", \"description\": \"round, small; has a small hole in the center\", \"similar objects\": [\"papertowel\", \"faucet\", \"coaster\"]}"}, {"object": "pottery", "object_id": 840, "gpt3_output": "\n\n{\"type\": \"pot\", \"description\": \"green, has a handle\", \"similar objects\": [\"dish\", \"potato\", \"candy\"]}"}, {"object": "pouch", "object_id": 841, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"pouch\", \"description\": \"round, has a handle\", \"similar objects\": [\"fishing net\", \"crate\"]"}, {"object": "power_shovel", "object_id": 842, "gpt3_output": "\n\n{\"type\": \"tool\", \"description\": \"round, has a handle\", \"similar objects\": [\"bunny\", \"harpoon\", \"spade\"]"}, {"object": "prawn", "object_id": 843, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"prawn\", \"gravy\", \"chicken\"]}"}, {"object": "pretzel", "object_id": 844, "gpt3_output": "\n\n{\"type\": \"baked goods\", \"description\": \"round, has a hole in the center\", \"similar objects\": [\"p Pretzel \", \"chocolate\", \"coke\"]}"}, {"object": "printer", "object_id": 845, "gpt3_output": "\n\nThe objects in the input could be objects that are used for input, like objects in a project or objects that are used for themselves. The objects in the input could also be used as sources of input, like when someone talks about \"type\" in a text editor."}, {"object": "projectile_(weapon)", "object_id": 846, "gpt3_output": "\n\nAn object that is movement-based, with a specific trajectory that can be controlled by a game engine."}, {"object": "projector", "object_id": 847, "gpt3_output": "\n\n{\"type\": \"electronic device\", \"description\": \"round; could be used for light and sound\", \"similar objects\": [\"computer\", \"laptop\", \"television\"]}"}, {"object": "propeller", "object_id": 848, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for propellers is the model's ability to identify propellers."}, {"object": "prune", "object_id": 849, "gpt3_output": "\n\n{\"type\": \"nut\", \"description\": \"red; has a pit and a skin; can be cut into small pieces\", \"similar objects\": [\"fig\", \"fruit\", \"grape\"]}"}, {"object": "pudding", "object_id": 850, "gpt3_output": "\n\n{\"type\": \"dessert\", \"description\": \"sugar, flour, butter\", \"similar objects\": [\"mango\", \"chocolate\", \"apple\"]}"}, {"object": "puffer_(fish)", "object_id": 851, "gpt3_output": "\n\n{\"type\": \"watermelon\", \"description\": \"\", \"similar objects\": [\"gummi bear\", \"giant watermelon\"]}"}, {"object": "puffin", "object_id": 852, "gpt3_output": "\n\n{\"type\": \"bird\", \"description\": \"black, white, short tail; could have a beak\", \"similar objects\": [\"giraffe\", \"seagull\", \"chick\"]}"}, {"object": "pug-dog", "object_id": 853, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"pug\", \"cat\"]}"}, {"object": "pumpkin", "object_id": 854, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "puncher", "object_id": 855, "gpt3_output": "\n\n{\"type\": \"tool\", \"description\": \"round, has a chisel and a chisel handle\", \"similar objects\": [\"butterfly\", \"thunderbolt\", \"iaudium\"]}"}, {"object": "puppet", "object_id": 856, "gpt3_output": "\n\nThe object detection model should focus on finding objects with similar characteristics that are associated with each of the five objects in the input. The model should also be able to identify different types of objects from the types of objects found in the input."}, {"object": "puppy", "object_id": 857, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "quesadilla", "object_id": 858, "gpt3_output": "\n\n{\"type\": \"dessert\", \"description\": \"sugar, cinnamon, butter\", \"similar objects\": [\"doughnut\", \"chocolate cake\", \"fruitcake\"]}"}, {"object": "quiche", "object_id": 859, "gpt3_output": "\n\n{\"type\": \"dessert\", \"description\": \"mango, raspberry, blueberry\", \"similar objects\": [\"mango\", \"raspberry\", \"blueberry\"]}"}, {"object": "quilt", "object_id": 860, "gpt3_output": "\n\n{\"type\": \"quilt\", \"description\": \"round, has a fabric on top\", \"similar objects\": [\"quilt top\", \"quilt\"]"}, {"object": "rabbit", "object_id": 861, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black and white, has a short tail\", \"similar objects\": [\"toucan\", \"parrot\", \"clam\", \"gazelle\"]}"}, {"object": "race_car", "object_id": 862, "gpt3_output": "\n\n{\"type\": \"car\", \"description\": \"black, red, yellow\", \"similar objects\": [\"car\", \"race car\", \"truck\"]}"}, {"object": "racket", "object_id": 863, "gpt3_output": "\n\nRacket is a tool that can be used for playing games, making music, or making other sounds. It has a hardwood board on one end and a plastic end with a plastic racket on the other."}, {"object": "radar", "object_id": 864, "gpt3_output": "\n\nThe focus of an object detection model's work should be on specific objects that are consistently represented in the data. In other words, objects that are specific to the model's type should be the focus of the model's work."}, {"object": "radiator", "object_id": 865, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"round, has a handle\", \"similar objects\": [\"sink\", \"radiator\", \"bathtub\", \"toilet\"]"}, {"object": "radio_receiver", "object_id": 866, "gpt3_output": "\n\nThe input should focus on specific features that an object detection model can detect. The input should also include a description of the features that it can detect."}, {"object": "radish", "object_id": 867, "gpt3_output": "\n\nThere are many different features that an object detection model could focus on. An object detection model should focus on those features that are most important for the input."}, {"object": "raft", "object_id": 868, "gpt3_output": "\n\n{\"type\": \"boat\", \"description\": \"black, with a white/black stripe down the middle\", \"similar objects\": [\"coaster\", \"raft\", \"rafting party\"]}"}, {"object": "rag_doll", "object_id": 869, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \" Rag Doll \", \"description\": \"A rag doll is a toy that is made of cloth, straw, or other material. The doll has a round head and a round body. It is often given to children as a toy because it is easy to hold and is not like other things that are around them. The rag doll is also a popular toy for girls.\""}, {"object": "raincoat", "object_id": 870, "gpt3_output": "\n\n{\"type\": \"appearance\", \"description\": \"round, with a shaven head\", \"similar objects\": [\"hat\", \"eyebrow\", \"sunglasses\"]}"}, {"object": "ram_(animal)", "object_id": 871, "gpt3_output": "\n\n{\"type\": \" ram \", \"description\": \"\", \"similar objects\": [\"\", \"lion\", \"giraffe \", \"monkey\"]}"}, {"object": "raspberry", "object_id": 872, "gpt3_output": "\n\n{\"type\": \"noun\", \"description\": \"a sweet fruit\", \"usage\": \"consumption\", \"similar objects\": [\"raspberry\", \"apple\"]}"}, {"object": "rat", "object_id": 873, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"rat\", \"otter\", \"gazelle\"]}"}, {"object": "razorblade", "object_id": 874, "gpt3_output": "\n\nThere are many different objects that can be looked for in objects that have been identified as zucchini. The features that could be looked for include cylindrical, smooth, and round. The features that have a brown and rough stem could be looked for, as well as slices and rounds."}, {"object": "reamer_(juicer)", "object_id": 875, "gpt3_output": "\n\nThe features that should be focus for an object detection model that processes objects of type vegetable would be:\n\n-The object's type\n-The object's size\n-The object's color\n-The object's shape"}, {"object": "rearview_mirror", "object_id": 876, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"Frontal Lobster\"},\n\n{\"type\": \"item\", \"name\": \"Backpack of Lobster\"},\n\n{\"type\": \"item\", \"name\": \"Soup of Lobster\"},\n\n{\"type\": \"item\", \"name\": \"Frozen Lobster\"},\n\n{\"type\": \"item\", \"name\": \"Frozen Lobster\"},\n\n{\"type\": \"item\", \"name\": \"Frozen Lobster\"},\n\n{\"type\": \"item\", \"name\": \"Frozen Lobster\"},\n\n{\"type\": \"item"}, {"object": "receipt", "object_id": 877, "gpt3_output": "\n\n{\"type\": \"item\", \"description\": \"red, with a cross\", \"similar objects\": [\"cross\", \"baked good\", \"cake\"], \"similar objects\": [\"trucker\", \"car\", \"tiremaker\"]}"}, {"object": "recliner", "object_id": 878, "gpt3_output": "\n\n{\"type\": \"bed\", \"description\": \"black, with a red upholstery\", \"similar objects\": [\"bed\", \"towel\"]}"}, {"object": "record_player", "object_id": 879, "gpt3_output": "\n\n{\"type\": \"record\", \"description\": \"red; has a groove\", \"similar objects\": [\"playground\", \"tape\", \"disc\"]}"}, {"object": "reflector", "object_id": 880, "gpt3_output": "\n\nThe reflector should focus on objects with a light color, such as red, round objects,. The mirror should also focus on objects, such as green, cylindrical objects, and objects with rough stems, such as cucumbers and eggs."}, {"object": "remote_control", "object_id": 881, "gpt3_output": "\n\nThere are many different types of object detection models that could be used for an input of zucchini, apple, ambulance, lightening, and remote control."}, {"object": "rhinoceros", "object_id": 882, "gpt3_output": "\n\n{\"type\": \" animal \", \"description\": \"light brown, black, smooth skin; thick fur; big horns; big tusks\", \"similar objects\": [\"bison\", \"giraffe \", \" elephant \", \" rhinoceros\"]}"}, {"object": "rib_(food)", "object_id": 883, "gpt3_output": "\n\nThe feature of an object that an object detection model should focus on is the shape of the object. An object's shape should be can be \n\nround, round, or smooth."}, {"object": "rifle", "object_id": 884, "gpt3_output": "\n\nThe objects that should be focus of an object detection model for a given input are those that have a smooth surface (such as zucchini or vegetables), could be cylindrical (such as a zebra or bean), and could have green or rough stems (such as a rifle or light lamp)."}, {"object": "ring", "object_id": 885, "gpt3_output": "\n\n{\"type\": \"ring\", \"description\": \"thick, white, has a band of perforations\", \"similar objects\": [\"ring\", \"necklace\", \"bangle\"]}"}, {"object": "river_boat", "object_id": 886, "gpt3_output": "\n\n{\"type\": \"vessel\", \"description\": \"black, white, and green; could have a chine on the stem\", \"similar objects\": [\"coaster\", \"car\", \"towel\"]"}, {"object": "road_map", "object_id": 887, "gpt3_output": "\n\nThere are many different features an object detection model could focus on, such as the following:\n\nInput: zucchini, Output: {\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}\n\nInput: zebra, Output: {\"type\": \"animal\", \"description\": \"black and white stripes; has a long mane\", \"similar objects\": [\"horse\", \"giraffe"}, {"object": "robe", "object_id": 888, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves \"\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "rocking_chair", "object_id": 889, "gpt3_output": "\n\n{\"type\": \"chair\", \"description\": \"black and white, has a backrest\", \"similar objects\": [\"couch\", \"sofa\", \"bed\"]}"}, {"object": "rodent", "object_id": 890, "gpt3_output": "\n\nThere are many different objects that can be looked for in objects that have the same features, such as zucchini and vegetables. It is important to focus on those objects that have the same features, such as rats and vehicles."}, {"object": "roller_skate", "object_id": 891, "gpt3_output": "\n\n{\"type\": \"skater\", \"description\": \"a type of skateboard\", \"similar objects\": [\"roller skates\", \"roller skateboards\", \"snowboarding\", \"bouldering\", \"climbing\", \"snowboarding\", \"tennis\", \"tennis\", \"tennis balls\", \"tennis rack\", \"tennis court\", \"tennis court system\", \"tennis court system system\", \"tennis court system system system\", \"tennis court system system system system\", \"tennis court system system system system\", \"tennis court system system system system\", \"tennis court"}, {"object": "Rollerblade", "object_id": 892, "gpt3_output": "\n\nThere are many different objects that can be used with a Rollerblade, including vegetables, fruits, tools, and machines. Each of these objects has different features that should be considered when designing an object detection model for the input. These features should include:\n"}, {"object": "rolling_pin", "object_id": 893, "gpt3_output": "\n\n{\"type\": \"dessert\", \"description\": \"mango, honey, cinnamon\", \"similar objects\": [\"dessert\", \"fruit\", \"chocolate\"]}"}, {"object": "root_beer", "object_id": 894, "gpt3_output": "\n\n{\"type\": \"drink\", \"description\": \"a drink made from a root beer can and root beer can bebened\", \"similar objects\": [\"root beer\", \"root can\", \"root beer can\"]"}, {"object": "router_(computer_equipment)", "object_id": 895, "gpt3_output": "\n\n{\"type\": \"computer\", \"description\": \"round, has a number of buttons\", \"similar objects\": [\"router\", \"laptop\", \"tablet\"]}"}, {"object": "rubber_band", "object_id": 896, "gpt3_output": "\n\n{\"type\": \"determinable\", \"description\": \"not stated\", \"similar objects\": [\"tape\", \"rubber band\"]}"}, {"object": "runner_(carpet)", "object_id": 897, "gpt3_output": "\n\n{\"type\": \"running tool\", \"description\": \"round; can run quickly and smoothly\", \"similar objects\": [\"running shoe\", \"running ball\", \"running cat\"]}"}, {"object": "plastic_bag", "object_id": 898, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"Plastic Bag\"},\n\n{\"type\": \"object\", \"name\": \" plastic bag\"},"}, {"object": "saddle_(on_an_animal)", "object_id": 899, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for saddle (on an animal) is the animal's surface. This will include anything from the animal's surface up to the saddle, and will include anything from looking for animals to finding objects."}, {"object": "saddle_blanket", "object_id": 900, "gpt3_output": "\n\n{\"type\": \"blank\", \"description\": \"\", \"similar objects\": [\"blank\", \"blank\", \"blank\"]"}, {"object": "saddlebag", "object_id": 901, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"Saddlebag\", \"description\": \"\n\n\n\nThe features of an object detection model that is detecting objects forage will focus on the following:\n\n-Determining the type of the object\n-Determining the style of the object\n-Determining the color of the object\n-Determining the shape of the object"}, {"object": "safety_pin", "object_id": 902, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"nothingness; has no use for its own metal\", \"similar objects\": [\"pens\", \"icicle\", \"safety pin\"]"}, {"object": "sail", "object_id": 903, "gpt3_output": "\n\n{\"type\": \" sails \", \"description\": \"white, with a blue or green band across the top\", \"similar objects\": [\"sail\", \"sailing boat\", \"sailing ship\"]}"}, {"object": "salad", "object_id": 904, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "salad_plate", "object_id": 905, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"zucchini\", \"tortilla\", \"tomato\"]}"}, {"object": "salami", "object_id": 906, "gpt3_output": "\n\nSalami is a type of cheese that is typically made from pork. The cheese is made by grating cheese and then adding salt and spices."}, {"object": "salmon_(fish)", "object_id": 907, "gpt3_output": "\n\n{\"type\": \"fish\", \"description\": \"black and white, scales smooth\", \"similar objects\": [\"grouper\", \"seaweed\", \"bacon\", \"chicken\"]}"}, {"object": "salmon_(food)", "object_id": 908, "gpt3_output": "\n\n{\"type\": \"fish\", \"description\": \"bluish body; scales smooth\", \"similar objects\": [\"grouper\", \"seaweed\", \"bluestreak\"]}"}, {"object": "salsa", "object_id": 909, "gpt3_output": "\n\n{\"type\": \"dessert\", \"description\": \"sour cream and jelly\", \"similar objects\": [\"frozen yogurt\", \"chocolate cake\", \"frozen fruit\", \"frozen vegetables\"]}"}, {"object": "saltshaker", "object_id": 910, "gpt3_output": "\n\n{\"type\": \"salt\", \"description\": \"white, with a blue or green color\", \"similar objects\": [\"salt and pepper\", \"salt and pepper bottle\"]}"}, {"object": "sandal_(type_of_shoe)", "object_id": 911, "gpt3_output": "\n\n{\"type\": \"outlet\", \"description\": \"empty\", \"similar objects\": [\"sandal\"]}"}, {"object": "sandwich", "object_id": 912, "gpt3_output": "\n\nThe objects in the input could be objects that are all objects, or they could be objects that have an object side by side. The features of the model that should focus on for an input with that name are: cylindrical, smooth, has green and rough stems, can be sliced into round pieces, has green leaves, similar objects."}, {"object": "satchel", "object_id": 913, "gpt3_output": "\n\n{\"type\": \"satchel\", \"description\": \"black, with a small opening at the bottom\", \"similar objects\": [\"purse\", \"wallet\", \"keyboard\"]"}, {"object": "saucepan", "object_id": 914, "gpt3_output": "\n\n{\"type\": \"dish\", \"description\": \"pale yellow, has a round cover\", \"similar objects\": [\"onion\", \"butterfly\", \"mango\"]}"}, {"object": "saucer", "object_id": 915, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, smooth; has a small hole in the middle\", \"similar objects\": [\"zucchini\", \"carrot\", \"zucchini stalk\"]}"}, {"object": "sausage", "object_id": 916, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black and white stripes; has a long mane\", \"similar objects\": [\"horse\", \"giraffe\", \"elephant\"]}"}, {"object": "sawhorse", "object_id": 917, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for evidence of life is its ability to identify similar objects. An object detection model that is looking for evidence of life should be able to identify that an object is a medical device, such as the sawhorse, because it has the ability to identify similar objects as being like a medical device."}, {"object": "saxophone", "object_id": 918, "gpt3_output": "\n\nThe input should be a saxophone."}, {"object": "scale_(measuring_instrument)", "object_id": 919, "gpt3_output": "\n\n{\"type\": \"scale\", \"description\": \"round, has a handle\", \"similar objects\": [\"treadmill\", \"instrument\", \"math instrument\"]"}, {"object": "scarecrow", "object_id": 920, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for scared objects is its ability to find scared objects. This includes things like scarecrows, which have a small red circle as their type, and scarecrows that have a big red circle as their type."}, {"object": "scarf", "object_id": 921, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"s scarf \", \"description\": \"s scarf is round, has a smooth surface, and has a white border\"."}, {"object": "school_bus", "object_id": 922, "gpt3_output": "\n\n{\"type\": \"bus\", \"description\": \"black, with red and green stripes\", \"similar objects\": [\"bushel\", \"pile of seeds\", \"bus\"]"}, {"object": "scissors", "object_id": 923, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for Vegetables is whether or not the object is cylindrical, with a smooth surface. The object should also be possible to identify by its similar objects."}, {"object": "scoreboard", "object_id": 924, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for evidence of an input is evidence of whether or not the object is similar to an input. An object detection model that is looking for evidence of an input should also be able to found whether or not the object is edible."}, {"object": "scraper", "object_id": 925, "gpt3_output": "\n\nScraper should focus on deep-cleaning dishes and pots, not on cleaning individual items."}, {"object": "screwdriver", "object_id": 926, "gpt3_output": "\n\n{\"type\": \"tool\", \"description\": \"deep; has a small hole on the top\", \"similar objects\": [\"pump\", \"pump\", \"pump\", \"lamp\"]"}, {"object": "scrubbing_brush", "object_id": 927, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is scrubbing is the model's ability to remove dirt, sand, and other debris from an object. The model should be able to clean surfaces by scrubbing down the sides and bottom."}, {"object": "sculpture", "object_id": 928, "gpt3_output": "\n\nThe feature of an object that needs to be considered for a featureless model is its size. Size is important because it is used to determine how the object will look and feel in the model. A small object will likely look large in the model and a large object will likely look small in the model."}, {"object": "seabird", "object_id": 929, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, or green; could have a beak and beaks\", \"similar objects\": [\"coaster\", \"falcon\", \"chick\"]}"}, {"object": "seahorse", "object_id": 930, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black and white, with a long mane\", \"similar objects\": [\"seagull\", \"whale\", \"toucan\"]}"}, {"object": "seaplane", "object_id": 931, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, smooth; could have rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"seaweed\", \"gulf land\", \"ocean\"]}"}, {"object": "seashell", "object_id": 932, "gpt3_output": "\n\nThe feature that should focus on for an input with a zucchini would be its type: zucchini, while the feature that should focus on for an input with a red wok would be its description: \"round; has a shining siren\"."}, {"object": "sewing_machine", "object_id": 933, "gpt3_output": "\n\n{\"type\": \"machine\", \"description\": \"round, has a speed control\", \"similar objects\": [\"needle\", \"stitch\", \"sewers\"]}"}, {"object": "shaker", "object_id": 934, "gpt3_output": "\n\n{\"type\": \"dish\", \"description\": \"pale, smooth, has a handle\", \"similar objects\": [\"onion\", \"cucumber\", \"gravy\"]}"}, {"object": "shampoo", "object_id": 935, "gpt3_output": "\n\n{\"type\": \"liquid\", \"description\": \"white, has a sour smell\", \"similar objects\": [\"soda\", \"shampoo\", \"conditioner\"]}"}, {"object": "shark", "object_id": 936, "gpt3_output": "\n\n{\"type\": \"fish\", \"description\": \"black, white, blurry\", \"similar objects\": [\"crocodile\", \"enlarged squid\", \"octopus\"]}"}, {"object": "sharpener", "object_id": 937, "gpt3_output": "\n\n{\"type\": \"ingredient\", \"description\": \"a sharpening stone\", \"similar objects\": [\"zester\", \"knife\", \"spice grinder\"]}"}, {"object": "Sharpie", "object_id": 938, "gpt3_output": "\n\n{\"type\": \"marker\", \"description\": \"round; has a line at the top\", \"similar objects\": [\"pen\", \"catcher's eye\", \"notch\", \"catcher's eye mark\"]}"}, {"object": "shaver_(electric)", "object_id": 939, "gpt3_output": "\n\nThe shaver (electric) should focus on objects with a light color, such as red, round objects, and objects with a stem, such as apples."}, {"object": "shaving_cream", "object_id": 940, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, smooth; could have bumps and crevices; could be cultivated in water; could be ground into a flour or sugarpaste\", \"similar objects\": [\"flour\", \"sugarpaste\", \" shaving cream \", \"apple\", \"banana\"]}"}, {"object": "shawl", "object_id": 941, "gpt3_output": "\n\n{\"type\": \"textbook\", \"description\": \"The model should focus on objects that are either specifically described as being like objects (e.g. a zucchini is like a vegetable), or have features that are similar to those of an object (e.g. a zebra has smooth skin and green stems, while a apple has round flesh and green leaves)."}, {"object": "shears", "object_id": 942, "gpt3_output": "\n\n{\"type\": \"mechanical tool\", \"description\": \"round, has a handle\", \"similar objects\": [\"pile of feathers\", \"pile of feathers\"]}"}, {"object": "sheep", "object_id": 943, "gpt3_output": "\n\n{\"type\": \"livestock\", \"description\": \"Sheep; could be divided intoiegel and dewelop; has two sets of legs and a two-tone coat\", \"similar objects\": [\"goat\", \" lamb \", \" pony \", \" horse \"}"}, {"object": "shepherd_dog", "object_id": 944, "gpt3_output": "\n\n{\"type\": \"dog\", \"description\": \"black and white, furrowed eyes; has a wagging tail\", \"similar objects\": [\"cat\", \" shepherd dog \", \"lion\"]}"}, {"object": "sherbert", "object_id": 945, "gpt3_output": "\n\nThere are many different features that an object detection model could focus on. One example is objects that are cylindrical, has smooth stem, and has round pieces."}, {"object": "shield", "object_id": 946, "gpt3_output": "\n\n{\"type\": \"armour\", \"description\": \"black, with a large hole in the middle\", \"similar objects\": [\"shield\", \"hat\", \"guitar\"]}"}, {"object": "shirt", "object_id": 947, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"shirt\", \"material\": \"steel\", \"similar objects\": [\"t-shirt\", \"cardigan\", \" skirt\"]}"}, {"object": "shoe", "object_id": 948, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"Shoe\", \"id\": \"Shoe\", \"is_custom\": 1, \"is_custom_intro\": 1, \"is_custom_title\": 1, \"is_custom_meta\": 1, \"is_custom_meta_title\": 1, \"is_custom_meta_title_1\": 1, \"is_custom_meta_title_2\": 1, \"is_custom_meta_title_3\": 1, \"is_custom_meta_title_4\": 1, \"is_custom_meta_title"}, {"object": "shopping_bag", "object_id": 949, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \" object \", \"description\": \"\n\nThere are many different features an object detection model could focus on, depending on the input. For example, an object detection model could focus on the type of object, the object's description, the similar objects, and the time of day the object is used."}, {"object": "shopping_cart", "object_id": 950, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves \"\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "short_pants", "object_id": 951, "gpt3_output": "\n\n{\"type\": \"text\", \"message\": \"You should only use objects that are safe\", \"similar objects\": [\"keyboard\", \"tongue\"]}"}, {"object": "shot_glass", "object_id": 952, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"x1\", \"accessory2\": \"x2\", \"accessory3\": \"x3\"}\n\nx1 = \"vegetable\", x2 = \"green\", x3 = \"black\"}\n\nx1 = \"vegetable\", x3 = \"black"}, {"object": "shoulder_bag", "object_id": 953, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"shoulder bag\", \"description\": \"black, with a white logo\", \"similar objects\": [\"purse\", \"backpack\", \"pouch\"]}"}, {"object": "shovel", "object_id": 954, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "shower_head", "object_id": 955, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"Shower Head\", \"description\": \"round, has a handle\", \"similar objects\": [\"shower\", \"hand\", \"shower head\"]}"}, {"object": "shower_cap", "object_id": 956, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"round, has a cap at the top\", \"similar objects\": [\"shower head\", \"shower curtain\"]}"}, {"object": "shower_curtain", "object_id": 957, "gpt3_output": "\n\n{\"type\": \"curtilage\", \"description\": \"thin, white, has a stem\", \"similar objects\": [\"curtilage\", \"paper\", \"shower curtain\"]}"}, {"object": "shredder_(for_paper)", "object_id": 958, "gpt3_output": "\n\n{\"type\": \"object\", \"properties\": [\"type\", \"properties\"]}"}, {"object": "signboard", "object_id": 959, "gpt3_output": "\n\n{\"type\": \"sign\", \"description\": \"round, has a circle at the center\", \"similar objects\": [\"house\", \"flag\", \"flagpole\"]}"}, {"object": "silo", "object_id": 960, "gpt3_output": "\n\n{\"type\": \"agricultural\", \"description\": \"round, has a roof\", \"similar objects\": [\"field\", \"cage\", \"straw\", \"milk can\"]}"}, {"object": "sink", "object_id": 961, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"\"}"}, {"object": "skateboard", "object_id": 962, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cyan, smooth; has a short stem\", \"similar objects\": [\"apple\", \"grocery store\", \"pumpkin\"]}"}, {"object": "skewer", "object_id": 963, "gpt3_output": "\n\n{\"type\": \"beef\", \"description\": \"round, has a sharp point\", \"similar objects\": [\"chicken\", \"fish\", \""}, {"object": "ski", "object_id": 964, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "ski_boot", "object_id": 965, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"round, has a strap\", \"similar objects\": [\"snow pants\", \"bunny earrings\", \"bunny earrings\"]"}, {"object": "ski_parka", "object_id": 966, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"black, with a red band around the neck\", \"similar objects\": [\"snowboard\", \"sunglasses\"]}"}, {"object": "ski_pole", "object_id": 967, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"round, has a handle\", \"similar objects\": [\"ski pole\", \"snow pants\"]}"}, {"object": "skirt", "object_id": 968, "gpt3_output": "\n\n{\"type\": \"textbook\", \"description\": \"The model should focus on objects that are similar in size, shape, or color to the input object. For example, the object might be a small, round, flat object that is similar in size to a pencil. The model should be able to create a story about what happened with the input object.\""}, {"object": "skullcap", "object_id": 969, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"light brown; has a brown band around the neck\", \"similar objects\": [\"moccasin\", \"sabre\", \"nosegay\"]}"}, {"object": "sled", "object_id": 970, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "sleeping_bag", "object_id": 971, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \" Sleeping bag \", \"description\": \"A sleeping bag is a product that is used to sleep in. A sleeping bag is made of soft fabric and has a lot of room to sleep. A sleeping bag is also made of for cold weather and is made of many pockets for items to keep with you. \" }"}, {"object": "sling_(bandage)", "object_id": 972, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"red; has a bandage; is water-resistant\"}\n\nInput:\n\n{\"type\": \"object\", \"description\": \"\"}"}, {"object": "slipper_(footwear)", "object_id": 973, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"small; has a small hole in the center\", \"similar objects\": [\"slipper\", \"sole\", \"shoe\"]}"}, {"object": "smoothie", "object_id": 974, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "snake", "object_id": 975, "gpt3_output": "\n\n{\"type\": \"insect\", \"description\": \"black, white, small; has a long body\", \"similar objects\": [\"crocodile\", \"gazelle\", \"elephant\", \"island\", \"island\", \"gazelle\", \"toucan\", \"parrot\", \"clam\", \"gazelle\", \"gazelle\", \"clam\", \"clam\", \"gazelle\", \"clam\", \"clam\", \"clam\", \"clam\", \"clam\", \"clam\", \"clam\", \"clam\", \"clam\","}, {"object": "snowboard", "object_id": 976, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for snowboards is the model's ability to identify snowboards. The snowboard model should be able to identify different types of snowboards, such as mogul, powder, and cedar."}, {"object": "snowman", "object_id": 977, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that sees a zucchini should be the zucchini's cylindrical shape, the zucchini's green color, and the zucchini's smooth surface. The model should be able to identify similar objects, such as a cucumber or an eggplant."}, {"object": "snowmobile", "object_id": 978, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"gray; has a large tail; can move through snow\", \"similar objects\": [\" sled \", \" snowmobile \", \" snow Taxi \", \" snow truck \"]"}, {"object": "soap", "object_id": 979, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"soup\", \"description\": \"\n\nThe features of an object detection model that focuses on those that are similar to an object should be:\n\n-Type: \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\"\n\n-Similar objects: [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "soccer_ball", "object_id": 980, "gpt3_output": "\n\n{\"type\": \"ball\", \"description\": \"light blue\", \"similar objects\": [\"ball\", \"ballerin\"]}"}, {"object": "sock", "object_id": 981, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"Sock\", \"quantity\": \"1\", \"similar objects\": [\"Fruit\", \"Bread\", \"Can\", \"Pot\", \"ettle\"]}"}, {"object": "sofa", "object_id": 982, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"sofia\", \"description\": \"\n\nSofia is a small, round object that has a small, round head. It is also small, round body and a small, round non-toxic head. Sofia has a small, round body and a small, round non-toxic head."}, {"object": "softball", "object_id": 983, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, smooth; could have rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"gazelle\", \"giraffe\", \" elephant\"]}"}, {"object": "solar_array", "object_id": 984, "gpt3_output": "\n\n{\"type\": \"geo-location\", \"location\": \"on a sunny beach\", \"similar objects\": [\"solar system\", \"geo-map\"]}"}, {"object": "sombrero", "object_id": 985, "gpt3_output": "\n\nThe object detection model should focus on finding objects with similar characteristics. For example, an object with a round body and a round head would be considered a vegetable. If the object had rough stems, it would be considered a animal."}, {"object": "soup", "object_id": 986, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "soup_bowl", "object_id": 987, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"zucchini\", \"butterfly\", \"fern\"]}"}, {"object": "soupspoon", "object_id": 988, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cyan, with a white spot in the center\", \"similar objects\": [\"zucchini\", \"butterfly\", \"toucan\"]}"}, {"object": "sour_cream", "object_id": 989, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, smooth; could have rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"sour cream\", \"butter\", \"grocery store], }"}, {"object": "soya_milk", "object_id": 990, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cyan; has a light green skin and a light brown body\", \"similar objects\": [\"soy milk\", \"chicken\", \"fedora\"]}"}, {"object": "space_shuttle", "object_id": 991, "gpt3_output": "\n\n{\"type\": \"space\", \"description\": \"round, has a surface\", \"similar objects\": [\"gate\", \"spaceship\", \"rocket\"]}"}, {"object": "sparkler_(fireworks)", "object_id": 992, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for evidence of life is the data available for examination. This data can include objects in the input, their type, description, and similar objects."}, {"object": "spatula", "object_id": 993, "gpt3_output": "\n\n{\"type\": \"apparatus\", \"description\": \"round, has a handle\", \"similar objects\": [\"spatula\", \"fork\", \"spatula-like tool\"]"}, {"object": "spear", "object_id": 994, "gpt3_output": "\n\n{\"type\": \"weapon\", \"description\": \"black; has a sharp point; could be used for stabbing\", \"similar objects\": [\"spear\", \"sword\", \" Baton \", \" knife \", \"gun\"]}"}, {"object": "spectacles", "object_id": 995, "gpt3_output": "\n\nThe features that should be focus for an object detection model that smells zucchini should be the cylindrical shape, the smooth surface, and the green color. The model should be able to identify zucchini as a vegetable, the description should be accurate, and the model should be able to identify the ingredients of zucchini as well as the type of zucchini."}, {"object": "spice_rack", "object_id": 996, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"spice rack\", \"description\": \"A rack of spices, typically a round object with a pointed end\", \"similar objects\": [\"flask\", \"fridge\", \"crate\"]}"}, {"object": "spider", "object_id": 997, "gpt3_output": "\n\n{\"type\": \"insect\", \"description\": \"black, white, small; has a webbing between its legs\", \"similar objects\": [\"jumping spider\", \"crawler\", \"moth\"]}"}, {"object": "crawfish", "object_id": 998, "gpt3_output": "\n\n{\"type\": \"fish\", \"description\": \"black and white, scales smooth\", \"similar objects\": [\"grouper\", \"seaweed\", \"gummed off\", \"urtega\", \"papaya\"]"}, {"object": "sponge", "object_id": 999, "gpt3_output": "\n\n{\"type\": \"ingredient\", \"description\": \"\"}"}, {"object": "spoon", "object_id": 1000, "gpt3_output": "\n\n{\"type\": \"ingredient\", \"description\": \"salt\", \"type\": \"vegetable\", \"size\": \"small\", \"similar objects\": [\"banana\", \"apple\", \"gravy\", \"chicken\"]}"}, {"object": "sportswear", "object_id": 1001, "gpt3_output": "\n\n{\"type\": \"item\", \"description\": \"black, white, red, green\", \"similar objects\": [\"shoe\", \"bra\", \"skate\"]}"}, {"object": "spotlight", "object_id": 1002, "gpt3_output": "\n\n{\"type\": \"tool\", \"description\": \"round; could have a lighted effect\", \"similar objects\": [\"light stick\", \"lamp\", \"umbrella\"]"}, {"object": "squid_(food)", "object_id": 1003, "gpt3_output": "\n\nThe zucchini and the apple should be focused on in this input. The zebra and the green bean should be focused on in this input. The ambulance and the light tool should be focused on in this input. The squid and the banana should be focused on in this input. The squid and the pan should be focused on in this input. The ambulance and the frying pan should be focused on in this input."}, {"object": "squirrel", "object_id": 1004, "gpt3_output": "\n\n{\"type\": \"insect\", \"description\": \"black, white, small; has a tail\", \"similar objects\": [\" squirrel \", \" rat \", \" snake \"], \"habit\": \" squirrel \n\n}"}, {"object": "stagecoach", "object_id": 1005, "gpt3_output": "\n\nThe ambulance could be an ambulance, the vehicle could be a bus, the stagecoach could be a bus, and the lantern could be a light bulb."}, {"object": "stapler_(stapling_machine)", "object_id": 1006, "gpt3_output": "\n\nStapler (stapler)."}, {"object": "starfish", "object_id": 1007, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black and white, has a sharp spade-like nose\", \"similar objects\": [\"star\", \"crocodile\", \"toucan\"]}"}, {"object": "statue_(sculpture)", "object_id": 1008, "gpt3_output": "\n\nThe feature of the statue (sculpture) should be focused on in an object detection model. The statue should have a smooth surface, be of a green color, and be smooth stems. The statue should be sliced into round pieces and its features should be similar to others in the input."}, {"object": "steak_(food)", "object_id": 1009, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, smooth; could have rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"beef\", \"chicken\", \"gravy\", \"pork\"]}"}, {"object": "steak_knife", "object_id": 1010, "gpt3_output": "\n\n{\"type\": \" knife \", \"name\": \" steak knife\"}, {\"type\": \" knife \", \"name\": \" steak\", \"weight\": \" steak\", \"velocity\": \" steak\", \"flinch rate\": \" steak\", \"recidivism\": \" steak\"}\n\nInput: screwdriver, Output: \n\n{\"type\": \" tool \", \"name\": \" screwdriver\"}, {\"type\": \" tool \", \"name\": \" screw\", \"weight\": \" screw\", \"velocity\": \" screw\", \"flinch rate\": \" screw\", \"recidivism\": \" screw\"}"}, {"object": "steering_wheel", "object_id": 1011, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for danger in an input such as a zucchini would be the steering wheel. This would be the tool that controls the vehicle and could have control over the siren and stretcher feature."}, {"object": "stepladder", "object_id": 1012, "gpt3_output": "\n\n{\"type\": \"weapon\", \"description\": \"black, with a black blade and a black handle\", \"similar objects\": [\"mace\", \" Knife \", \" axe \"],"}, {"object": "step_stool", "object_id": 1013, "gpt3_output": "\n\n{\"type\": \"platform\", \"positioning parameter\", \"parameters\", \"description\": \"The step stool should be able to be placed in any position so that users can reach up and reach for things that they need to eat or drink. The platform should also have a handle so that users can easily go up and down the steps.\""}, {"object": "stereo_(sound_system)", "object_id": 1014, "gpt3_output": "\n\n{\"type\": \"sound system\", \"description\": \"round, has a speaker\", \"similar objects\": [\"speakers\", \"mic\", \"mic stand\", \" Cochlear B ears \", \"hearing aid\"]}"}, {"object": "stew", "object_id": 1015, "gpt3_output": "\n\n{\"type\": \"taste\", \"taste\", \"completed\", \"completed\"}, \"completed\": true"}, {"object": "stirrer", "object_id": 1016, "gpt3_output": "\n\n{\"type\": \"drum\", \"description\": \"round; has a spindle\", \"similar objects\": [\"drummer\", \"harpoon\"]"}, {"object": "stirrup", "object_id": 1017, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"a piece of metal or plastic that helps a person wear a shoe\", \"similar objects\": [\"tirejarret\", \"sunglasses\", \"sunglasses case\"]}"}, {"object": "stool", "object_id": 1018, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"stool\", \"description\": \"black, has a handle\", \"similar objects\": [\"cage\", \"tower\", \"timbuk2\"]}"}, {"object": "stop_sign", "object_id": 1019, "gpt3_output": "\n\nThere are many different features that object detection models could focus on. One example is that of items that have similar shapes or objects that have the same size. Another example is an object's age or size."}, {"object": "brake_light", "object_id": 1020, "gpt3_output": "\n\nThe features that should be focus for an object detection model that smells like zucchini would be the features that make zucchini a vegetable, such as cylindrical shape, smooth surface, and possible brown and rough stems, all of which would be shared by other objects in the input.\n\nThe features that should focus for an object detection model that smells like the zebra would be the similar objects, such as a cucumber,, eggplant, and green bean."}, {"object": "stove", "object_id": 1021, "gpt3_output": "\n\n{\"type\": \"fuel\", \"description\": \"flammable; has a smell\", \"similar objects\": [\"coke\", \"petrol\", \"gasoline\"]}"}, {"object": "strainer", "object_id": 1022, "gpt3_output": "\n\n{\"type\": \"filter\", \"description\": \" should be able to handle a variety of media\"}, \"similar objects\": []"}, {"object": "strap", "object_id": 1023, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"\"}"}, {"object": "straw_(for_drinking)", "object_id": 1024, "gpt3_output": "\n\n{\"type\": \"ingredient\", \"description\": \"flowers; needs to be sweetened\", \"similar objects\": [\"frozen fruit\", \"chocolate\", \"frozen yogurt\"]}"}, {"object": "strawberry", "object_id": 1025, "gpt3_output": "\n\n{\"type\": \"fruit\", \"description\": \"red, round, has a stem\", \"similar objects\": [\"apple\", \"banana\", \"pear\"]}"}, {"object": "street_sign", "object_id": 1026, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for signs of life is the object's size. For vegetables, it would focus on their large seeds and for fruits on the seeds andalinage. For vehicles it would look for signs of life such as a driver and passengers."}, {"object": "streetlight", "object_id": 1027, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for signs of life is the environment. This includes not just the physical environment but also the conditions for using the environment, such as being in the sun or rain. This will help to determine if the object is livingable."}, {"object": "string_cheese", "object_id": 1028, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for cheese is its size. Other features that might be important for the model to focus on include its shape, size, and color."}, {"object": "stylus", "object_id": 1029, "gpt3_output": "\n\nThe stylus is a simple input that needs to be able to connect to an application to make notes."}, {"object": "subwoofer", "object_id": 1030, "gpt3_output": "\n\n{\"type\": \"mic\", \"description\": \"round, has a hole in the middle\", \"similar objects\": [\"microwave\", \"microphone\", \"sig\"],"}, {"object": "sugar_bowl", "object_id": 1031, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"Sugar Bowl\", \"description\": \"\", \"size\": \"\", \"type\": \"vegetable\", \"properties\": [\"name\", \"description\"]"}, {"object": "sugarcane_(plant)", "object_id": 1032, "gpt3_output": "\n\n{\"type\": \"plant\", \"description\": \"black, red, green; can be red, green, and brown; can have a stem\", \"similar objects\": [\"sugar\", \"cane\", \"canary\"]}"}, {"object": "suit_(clothing)", "object_id": 1033, "gpt3_output": "\n\n{\"type\": \"item\", \"description\": \"I don't know\", \"similar objects\": [\"frock\"]}"}, {"object": "sunflower", "object_id": 1034, "gpt3_output": "\n\n{\"type\": \"flower\", \"description\": \"green, has a stem\", \"similar objects\": [\"honeydew\", \"lily\", \"violet\"]}"}, {"object": "sunglasses", "object_id": 1035, "gpt3_output": "\n\nThe features that should be focus for an object detection model that smells zucchini should be the cylindrical shape, the smooth surface, and the green color. The model should be able to identify zucchini as a food item, but should not be able to identify the product zucchini from other vegetables."}, {"object": "sunhat", "object_id": 1036, "gpt3_output": "\n\n{\"type\": \"image\", \"image\": [{\"z\": \"0\", \"x\":"}, {"object": "surfboard", "object_id": 1037, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cyan; has small, sharp teeth\", \"similar objects\": [\"seaweed\", \"grocery store\", \"bridge\"]}"}, {"object": "sushi", "object_id": 1038, "gpt3_output": "\n\nThe input should be a list of objects that are similar in shape, size, or color."}, {"object": "mop", "object_id": 1039, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves \"\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "sweat_pants", "object_id": 1040, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"suit\", \"description\": \"black, red, green; might have a waistband and pockets\"}\n\nInput: suit, Output: \n\n{\"type\": \"object\", \"name\": \"shirt\", \"description\": \"black, red, green; might have a waistband and pockets\"}"}, {"object": "sweatband", "object_id": 1041, "gpt3_output": "\n\n{\"type\": \"attribute\", \"attributeName\": \"value\", \"attributeValue\": [], \"source\": \"Human\"."}, {"object": "sweater", "object_id": 1042, "gpt3_output": "\n\n{\"type\": \"item\", \"description\": \"green, has a handle\", \"similar objects\": [\"chaat\", \"chocolate\", \"bars\", \"cake\"]}"}, {"object": "sweatshirt", "object_id": 1043, "gpt3_output": "\n\n{\"type\": \"text\", \"message\": \"I'm not sure\", \"similar objects\": [\"tshirt\", \"hoodie\"]}"}, {"object": "sweet_potato", "object_id": 1044, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, smooth; can have bumps and bruises\", \"similar objects\": [\"apple\", \"carrot\", \"zucchini\"]}"}, {"object": "swimsuit", "object_id": 1045, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves \"\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "sword", "object_id": 1046, "gpt3_output": "\n\n{\"type\": \"weapon\", \"description\": \"black; has a blade that can be sharpened\", \"similar objects\": [\"sword\", \"spear\", \" Baton \", \"nightstick\"]}"}, {"object": "syringe", "object_id": 1047, "gpt3_output": "\n\n{\"type\": \"vitamins\", \"description\": \" needed for health; can be shared with others; can be shared using exchange rates\"}"}, {"object": "Tabasco_sauce", "object_id": 1048, "gpt3_output": "\n\n{\"type\": \"text\", \"message\": \"\n\nThe zucchini should be green because it will be cooked by the fire. The avocado should have a smooth surface because it will be sliced into round pieces. The eggplant should have green leaves to keep its color and the green bean should be able to have green leaves because they are going to be cooked by the fire."}, {"object": "table-tennis_table", "object_id": 1049, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for tennis players is their body size. This model should be able to identify players of all body types, regardless of their size."}, {"object": "table", "object_id": 1050, "gpt3_output": "\n\n{\"type\": \"table\", \"description\": \"black, with a white line in the center\", \"similar objects\": [\"cat\", \"coaster\", \"coaster\"]"}, {"object": "table_lamp", "object_id": 1051, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for dinner is the object's size. For vegetables, they should focus on the most round and small-sized vegetables, while for fruits they should look for plants that have similar growth habits (such as apples or bananas). For flowers, they should focus on those that have round flowers and those that have blue or green leaves."}, {"object": "tablecloth", "object_id": 1052, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for food is the tablecloth. This tablecloth can help an object detection model find food because it can help an image show the object's surroundings. The tablecloth can also help an object detection model determine if the object is food."}, {"object": "tachometer", "object_id": 1053, "gpt3_output": "\n\nThe output of an object detection model should be able to measure the intensity of light, while the input should be able to find objects."}, {"object": "taco", "object_id": 1054, "gpt3_output": "\n\n{\"type\": \"taco\", \"description\": \"red, smooth, has a toppings of guacamole and cheese\", \"similar objects\": [\"taco\", \"chicken\", \"fish\", \"chicken salad\", \"dessert chicken\"]}"}, {"object": "tag", "object_id": 1055, "gpt3_output": "\n\nThe feature that should focus on for an input with a specific name is \"type\". An object with the type feature should be able to be identified by its type, such as a tag that can be identified by its type of light (such as a lantern)."}, {"object": "taillight", "object_id": 1056, "gpt3_output": "\n\nThe features that should be focus for an object detection model that smells zucchini should be the cylindrical shape, the smooth surface, and the green color. The model should be able to identify zucchini as a vegetable, the description should be accurate, and the model should be able to identify the ingredients of zucchini as well as the object's siblings."}, {"object": "tambourine", "object_id": 1057, "gpt3_output": "\n\n{\"type\": \"guitar\", \"description\": \"a small, thin, pointed instrument with a thin metal wire in one end\", \"similar objects\": [\"guitar\", \"banjo\", \"mandolin\"]}"}, {"object": "army_tank", "object_id": 1058, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"red; has a long road surface; can be pushed or pulled\", \"similar objects\": [\"tank\", \"tank engine\", \"tank\", \", \"tank engine\", \"tank\", \"\", \"army tank\", \"army tank\", \"army tank\", \"army tank\", \"army tank\", \"army tank\", \"army tank\", \"army tank\", \"army tank\", \"army tank\", \"army tank\", \"army tank\", \"army tank\", \"army tank\", \"army tank\", \"arm"}, {"object": "tank_(storage_vessel)", "object_id": 1059, "gpt3_output": "\n\n{\"type\": \"tank\", \"description\": \"black, with a large hole in the bottom\", \"similar objects\": [\"furniture\", \"tank\", \"tank\"], \"similar objects\": [\"tank\", \"tank\", \"vessel\", \"container\"]"}, {"object": "tank_top_(clothing)", "object_id": 1060, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"Top\", \"description\": \"Belt-like item with a deep pocket\", \"similar objects\": [\"bottom\", \"tank\", \"gun\"]}"}, {"object": "tape_(sticky_cloth_or_paper)", "object_id": 1061, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for evidence of life is the ability to track the object's movement. An object's movement can help us determine if it is or is not a living thing."}, {"object": "tape_measure", "object_id": 1062, "gpt3_output": "\n\nThe ability to measure things accurately and quickly is important in our world. Object detection models should focus on detecting objects with similar characteristics, whether they be similar looking objects such as objects with similar shapes or similar features, or simply similar in size or shape. object detection models that focus on detecting objects with similar characteristics and similar features are more likely to be successful in detecting the presence of other objects, particularly in a search context."}, {"object": "tapestry", "object_id": 1063, "gpt3_output": "\n\nThe tapestry should focus on the details of the fabric, such as the color and style."}, {"object": "tarp", "object_id": 1064, "gpt3_output": "\n\n{\"type\": \"tarp\", \"description\": \"black, with a white stripe running along the top\", \"similar objects\": [\"tarp\", \"cage\", \"football\", \"soccer ball\"]"}, {"object": "tartan", "object_id": 1065, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for tartans is their size. Other features that could be used for an object detection model that is looking for tartans include their color, shape, or texture."}, {"object": "tassel", "object_id": 1066, "gpt3_output": "\n\nThe features that should be focus for an object detection model for a zucchini are its type, its description, its similar objects, and its handle."}, {"object": "tea_bag", "object_id": 1067, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"tea bag\", \"description\": \"},"}, {"object": "teacup", "object_id": 1068, "gpt3_output": "\n\n{\"type\": \"cup\", \"description\": \"green, has a handle\", \"similar objects\": [\"soup\", \"taco\", \"chicken\"]}"}, {"object": "teakettle", "object_id": 1069, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for food is the object's type. This includes types such as \"vegetable\", \"animal\", and \"food\"."}, {"object": "teapot", "object_id": 1070, "gpt3_output": "\n\n{\"type\": \"pot\", \"description\": \"green, has a handle\", \"similar objects\": [\"tea pot\", \"coaster\", \"soup can\"]}"}, {"object": "teddy_bear", "object_id": 1071, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black and red; could have a red fur\", \"similar objects\": [\"bear\", \"puppy\", \"toucan\"]}"}, {"object": "telephone", "object_id": 1072, "gpt3_output": "\n\n{\"type\": \"phone\", \"description\": \"black, with a red number on it\", \"similar objects\": [\"linen bag\", \"phone case\"]}"}, {"object": "telephone_booth", "object_id": 1073, "gpt3_output": "\n\n{\"type\": \"telephone\", \"description\": \"round, has a keypad\", \"similar objects\": [\"number\", \"phone\"]}"}, {"object": "telephone_pole", "object_id": 1074, "gpt3_output": "\n\n{\"type\": \"object\", \"position\": \"x\", \"size\": \"\", \"description\": \"small, round, has a handle\"}\n\n{\"type\": \"object\", \"position\": \"y\", \"size\": \"\", \"description\": \"small, round, has a stem\"}"}, {"object": "telephoto_lens", "object_id": 1075, "gpt3_output": "\n\n{\"type\": \"camera\", \"description\": \"round, has a long lens\", \"similar objects\": [\"telephone\", \"film\", \"photo camera\"]"}, {"object": "television_camera", "object_id": 1076, "gpt3_output": "\n\n{\"type\": \"camera\", \"description\": \"round, has a lens\", \"similar objects\": [\"television\", \"television show\"]}"}, {"object": "television_set", "object_id": 1077, "gpt3_output": "\n\n{\"type\": \"TV show\", \"description\": \"a round, cylindrical object\", \"similar objects\": [\"television\", \"television show\"]}"}, {"object": "tennis_ball", "object_id": 1078, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"red; has a small hole in the center\", \"similar objects\": [\"sock\", \"piano teacher\", \"guitar\"]}"}, {"object": "tennis_racket", "object_id": 1079, "gpt3_output": "\n\nThe object detection model should focus on finding objects with similar characteristics that are in the same category as the input. For example, an object that is described as a \"vegetable\" should be focused on finding objects that are that same type of vegetable."}, {"object": "tequila", "object_id": 1080, "gpt3_output": "\n\n{\"type\": \"liquor\", \"description\": \"red; has a sour taste\", \"similar objects\": [\"mango\", \"gin\"]}"}, {"object": "thermometer", "object_id": 1081, "gpt3_output": "\n\nThe ability to detect different types of objects in an input can be used to focus on different features. The features that should focus on in an object detection model for a zucchini can be: cylindrical, smooth, green, smooth, and round. The features that should focus on for an ambulance can be: black and white stripes, has a long mane, and has a shining siren."}, {"object": "thermos_bottle", "object_id": 1082, "gpt3_output": "\n\n{\"type\": \"bottle\", \"capacity\": \"\", \"price\": \"\", \"description\": \"\", \"similar objects\": [\"coaster\", \"fryer\", \"toaster\"]}"}, {"object": "thermostat", "object_id": 1083, "gpt3_output": "\n\nThe ability to control temperature in a controlled environment."}, {"object": "thimble", "object_id": 1084, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"small hole in handle\", \"similar objects\": [\"thimble\", \"spoon\"]}"}, {"object": "thread", "object_id": 1085, "gpt3_output": "\n\n{\"type\": \"thread\", \"description\": \"black, has a strong threading system\", \"similar objects\": [\"corduroy\", \"seamless web\", \"seaweed\"]}"}, {"object": "thumbtack", "object_id": 1086, "gpt3_output": "\n\nThe features that should be focus for an object detection model that smells zucchini should be the cylindrical shape, the smooth surface, and the green or green-like description."}, {"object": "tiara", "object_id": 1087, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"Tiara\", \"type\": \"item\"}, {\"type\": \"item\", \"name\": \"Tiara\", \"type\": \"item\"}"}, {"object": "tiger", "object_id": 1088, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, or light-colored; has a stripes or a pattern\", \"similar objects\": [\"giraffe\", \"toucan\", \"seagull\"]}"}, {"object": "tights_(clothing)", "object_id": 1089, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"Tights\", \"description\": \"\"}"}, {"object": "timer", "object_id": 1090, "gpt3_output": "\n\n{\"type\": \"timepiece\", \"description\": \"round, has a bezel and a chronograph movement\", \"similar objects\": [\"watch\", \"watch case\", \" Chronograph watch\"]"}, {"object": "tinfoil", "object_id": 1091, "gpt3_output": "\n\nThe input should focus on objects that are Tinfoil-like in shape or size."}, {"object": "tinsel", "object_id": 1092, "gpt3_output": "\n\nThere are many different features an object detection model could focus on, such as detecting that an object is not a vegetable, animal, or fruit, but should be considered for a list of possible features:\n\n-The object's type: this should be a type of object, such as a vegetable, animal, or fruit.\n-Your experience with using this object: do you know how to use it, such as how to put it together? Do you know what kind of light it gives? Do you know that it can have features on its stem and leaves that are not present on other objects?\n-The features"}, {"object": "tissue_paper", "object_id": 1093, "gpt3_output": "\n\nThe object detection model should focus on finding objects with similar characteristics that are in contact with each other. The model should also be able to identify different types of objects, such as vegetables and animals."}, {"object": "toast_(food)", "object_id": 1094, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for food is the object's size. For example, an ambulance would be looking for vehicles with siren and a stretcher would be looking for ones with light."}, {"object": "toaster", "object_id": 1095, "gpt3_output": "\n\n{\"type\": \"toaster\", \"description\": \"round, has a light at the end of it\", \"similar objects\": [\"toaster oven\", \"aidean oven\"]}"}, {"object": "toaster_oven", "object_id": 1096, "gpt3_output": "\n\n{\"type\": \"oven\", \"description\": \"yellow; has a hearth; can be turned into a oven\", \"similar objects\": [\"toaster\", \"fridge\", \"Refrigerator\"]"}, {"object": "toilet", "object_id": 1097, "gpt3_output": "\n\n{\"type\": \"room\", \"description\": \"round, has a bowl for a water bottle\", \"similar objects\": [\"bathroom\", \"toilet\", \"bath\", \"desk\"]}"}, {"object": "toilet_tissue", "object_id": 1098, "gpt3_output": "\n\n{\"type\": \"text\", \"message\": \"Please input a message\", \"similar objects\": [\"toilet paper\"]}"}, {"object": "tomato", "object_id": 1099, "gpt3_output": "\n\n{\"type\": \"fruit\", \"description\": \"red, has a stem\", \"similar objects\": [\"onion\", \"grape\", \"canary\"]}"}, {"object": "tongs", "object_id": 1100, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"x\"}"}, {"object": "toolbox", "object_id": 1101, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"toolbox\", \"description\": \"box with a tool inside\", \"similar objects\": [\"folder\", \"cabinet\", \"counter\", \"tables\", \"chairs\", \"falls asleep\", \"name\", \"noun\", \"vegetable\", \"noun\", \"vegetable\", \"vegetable\", \"vegetable\", \"vegetable\", \"vegetable\", \"vegetable\", \"vegetable\", \"vegetable\", \"vegetable\", \"vegetable\", \"vegetable\", \"vegetable\", \""}, {"object": "toothbrush", "object_id": 1102, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \" Toothbrush \", \"description\": \"\n\nThis object is focused on being able to detect objects with small, specific details. For an object with small details, like a toothbrush, object detection will not work well. The model should be able to handle more detailed objects, like toothbrushes, with enough detail that an object detection model would be able to detect it."}, {"object": "toothpaste", "object_id": 1103, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for candidates for a food source is the object's object detection model should focus on."}, {"object": "toothpick", "object_id": 1104, "gpt3_output": "\n\n{\"type\": \"dental toothpick\", \"description\": \"light brown, has a sharp point\", \"similar objects\": [\"dentist's tool\", \"tootie\", \"gum picker\"]}"}, {"object": "cover", "object_id": 1105, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"cover\", \"description\": \"A cover for a cooking tool. The cover could be made of materials like metal or plastic. The cover could also have a light or light-based decoration. The cover could also have a siren or stretcher to make it more visible.\""}, {"object": "tortilla", "object_id": 1106, "gpt3_output": "\n\n{\"type\": \"tortilla\", \"description\": \"red, smooth, has a hole in the center\", \"similar objects\": [\"tortilla\", \"chocolate\", \"frozen yogurt\"]}"}, {"object": "tow_truck", "object_id": 1107, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for zucchini is its size. This model should be able to find zucchini if it is large enough. Additionally, the model should be able to find zucchini if it is green and smooth. If the zucchini is sliced into round pieces, the model should be able to find zucchini."}, {"object": "towel", "object_id": 1108, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"Towel\", \"description\": \"Towel; has a towel head; could have a built-in towel rack\", \"similar objects\": [\" towel \", \" towel rack \", \" towel \"]"}, {"object": "towel_rack", "object_id": 1109, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"towel rack\", \"description\": \"A rack of towels, at least six feet long and six inches wide. The top of the rack is placed high enough so that the towels are well above the water level but not so high that the water covers the rack.\""}, {"object": "toy", "object_id": 1110, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves \"\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "tractor_(farm_equipment)", "object_id": 1111, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"red; has aizone; could be for sale\", \"similar objects\": [\" tractor \", \" truck \", \" car \"], \"related objects\": [\"car\", \" truck \", \" car \"], \"related objects\": [\"tractor \", \" truck \", \" car \"], \"related objects\": [\"tractor \", \" truck \", \" car \"], \"related objects\": [\"car\", \" truck \", \" car \"], \"related objects\": [\"tractor \", \" truck \", \" car \"], \"related objects\": [\"car\", \" truck \", \" car \"], \"related"}, {"object": "traffic_light", "object_id": 1112, "gpt3_output": "\n\nThe features that should be focus for an object detection model that smells zucchini should be the cylindrical shape, the smooth surface, and the green color. The model should be able to identify zucchini as a vegetable, the description should be accurate, and the model should be able to identify zucchini as being similar to other objects."}, {"object": "dirt_bike", "object_id": 1113, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"red; has a long wheelbase and a small body\", \"similar objects\": [\"car\", \"truck\", \"SUV\"]}"}, {"object": "trailer_truck", "object_id": 1114, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"red; has a signage on the side\", \"similar objects\": [\"car\", \"truck\", \"bogie\"]}"}, {"object": "train_(railroad_vehicle)", "object_id": 1115, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"red; has a track\", \"similar objects\": [\"train\", \"car\", \"bus\"]}"}, {"object": "trampoline", "object_id": 1116, "gpt3_output": "\n\n{\"type\": \"activities\", \"description\": \"should be able to stand and hold onto a handle\", \"similar objects\": [\"trampoline\", \"skydiving\", \"biking and running\", \"spinning and | spinning\", \"dancing\", \"unguiding things\"]}"}, {"object": "tray", "object_id": 1117, "gpt3_output": "\n\n{\"type\": \"tray\", \"description\": \"round, has a handle\", \"similar objects\": [\"fryer\", \"fry\", \"dishwasher\"]}"}, {"object": "trench_coat", "object_id": 1118, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"round, has a handle\", \"similar objects\": [\"piano key\", \"keyboard\"]"}, {"object": "triangle_(musical_instrument)", "object_id": 1119, "gpt3_output": "\n\nThe triangle (musical instrument) can be used for playing triangle songs or as a soundless support for a triangle book."}, {"object": "tricycle", "object_id": 1120, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"black, with a red stripe down the middle\", \"similar objects\": [\"car\", \"trolley\", \"bus\"]}"}, {"object": "tripod", "object_id": 1121, "gpt3_output": "\n\n{\"type\": \"camera\", \"description\": \"round, has a focus ring\", \"similar objects\": [\"telephone\", \"poster\", \"photo\"]}"}, {"object": "trousers", "object_id": 1122, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"T-shirt\", \"size\": \"S\", \"color\": \"white\", \"similar objects\": [\"bunny\", \"fairytale\"]}"}, {"object": "truck", "object_id": 1123, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"red; has atering system; could have broken windows\", \"similar objects\": [\"car\", \"truck\", \"SUV\"]}"}, {"object": "truffle_(chocolate)", "object_id": 1124, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"truffle\", \"chocolate\", \"frozen yogurt\"]}"}, {"object": "trunk", "object_id": 1125, "gpt3_output": "\n\n{\"type\": \"body\", \"description\": \"black, smooth, has a deep well\", \"similar objects\": [\"cat\", \"dog\", \"catcher's eye\"]}"}, {"object": "vat", "object_id": 1126, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for vegetable or animal objects is the size of the object. This should include objects such as tomatoes, onions, and other small onions. The size of the object should also include objects that are not vegetables or animals, such as cans and other cans."}, {"object": "turban", "object_id": 1127, "gpt3_output": "\n\nThe focus of an object detection model's focus should be on specific objects that are consistently represented in the data. Specific objects can be defined by their features, which are listed in the table below.\n\nInput: zucchini, Output:\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}\n\nInput: zebra, Output:\n\n{\"type\": \"animal\", \""}, {"object": "turkey_(food)", "object_id": 1128, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for food is the object's size. For vegetables, they should focus on the biggest and most round ones. For fruits, they should focus on the most red and large ones. For tools, they should look for those that have deep handles and are made of round materials. And for lanterns and lights, the larger the object the better."}, {"object": "turnip", "object_id": 1129, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "turtle", "object_id": 1130, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "turtleneck_(clothing)", "object_id": 1131, "gpt3_output": "\n\nThere are many different objects that can be detected with an object detection model. A turtleneck can be detected as being clothing, an animal, or a tool."}, {"object": "typewriter", "object_id": 1132, "gpt3_output": "\n\nThe input should be a list of objects that all have a common feature, such as an object with a round head or an object that is smooth."}, {"object": "umbrella", "object_id": 1133, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "underwear", "object_id": 1134, "gpt3_output": "\n\n{\"type\": \"item\", \"description\": \"red, with a white border\", \"similar objects\": [\"jacket\", \"underwear\", \"skirt\"]}"}, {"object": "unicycle", "object_id": 1135, "gpt3_output": "\n\nThere are many different objects that can be detected by an object detection model, depending on the input. The input could be a object, such as a zucchini, or a unicycle. The model could focus on those objects that have a smooth surface, such as zebra and apple."}, {"object": "urinal", "object_id": 1136, "gpt3_output": "\n\n{\"type\": \"urethane\", \"description\": \"round, has a hole in the center\", \"similar objects\": [\"urethane\", \"enamel\", \"iron\"]"}, {"object": "urn", "object_id": 1137, "gpt3_output": "\n\nThe feature that should focus on for an input with a specific type of object is the object's type. For example, an object that is called a \"vegetable\" is would be more likely to be found in a \"vegetable\" input than an \"animal\" input."}, {"object": "vacuum_cleaner", "object_id": 1138, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"round, has a hose at the top\", \"similar objects\": [\"auger\", \"vacuum cleaner\", \"hose\"]"}, {"object": "vase", "object_id": 1139, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for Vegetables is whether or not the object is cylindrical, with a smooth surface. The object should also be similar to other objects in the input, with a focus on whether or not it is black and white stripes."}, {"object": "vending_machine", "object_id": 1140, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for food is its ability to find other objects with similar characteristics. For example, if an ambulance was to find food, it would be able to identify and devour the food in the machine."}, {"object": "vent", "object_id": 1141, "gpt3_output": "\n\n{\"type\": \"vent\", \"description\": \"closed\", \"similar objects\": [\"vent\", \"chamber\"]}"}, {"object": "vest", "object_id": 1142, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"\"}"}, {"object": "videotape", "object_id": 1143, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for videos of objects is the presence of papers. This model would be interested in videos of objects that have been touched or even in videos of objects that have been in contact with other objects."}, {"object": "vinegar", "object_id": 1144, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for vinegar is its size. Other features that might be important for an object detection model to focus on include its shape, color, and texture."}, {"object": "violin", "object_id": 1145, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for evidence of life is its ability to identify objects that share similar features. Object detection models that are looking for evidence of an emergency should focus on finding objects that have the same features as an object that is under investigation."}, {"object": "vodka", "object_id": 1146, "gpt3_output": "\n\n{\"type\": \"alcohol\", \"description\": \"black, with a green \"spoon\" at the top\", \"similar objects\": [\"grape\", \"chocolate\", \"lime\"]}"}, {"object": "volleyball", "object_id": 1147, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "vulture", "object_id": 1148, "gpt3_output": "\n\nThe feature that should focus on for an input with a vulture is its size. The vulture is a large bird and its size should be important in the model's size range."}, {"object": "waffle", "object_id": 1149, "gpt3_output": "\n\n{\"type\": \"dessert\", \"description\": \"sugar, cinnamon, sugar\", \"similar objects\": [\"dessert\", \"chocolate\", \"dried fruit\"]}"}, {"object": "waffle_iron", "object_id": 1150, "gpt3_output": "\n\n{\"type\": \"electric device\", \"description\": \"red; has a lighted surface\", \"similar objects\": [\"gridiron\", \"coaster\", \"gasoline engine\"]}"}, {"object": "wagon", "object_id": 1151, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"red; has a wheel\", \"similar objects\": [\"car\", \"trolley\", \"bus\"]}"}, {"object": "wagon_wheel", "object_id": 1152, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"Wheel of Fortune\", \"description\": \"Tumbleweed; small; white; has a wheel on it\", \"similar objects\": [\"Wagon\", \"Camel\", \"Rabbit\"]}"}, {"object": "walking_stick", "object_id": 1153, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "wall_clock", "object_id": 1154, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for evidence of life is the time of day. An object that is found with time of day, such as a wall clock, could be more likely to have been made with the user in mind."}, {"object": "wall_socket", "object_id": 1155, "gpt3_output": "\n\n{\"type\": \"electrical object\", \"description\": \"electric\", \"similar objects\": [\"sockets\", \"pipes\", \" Fault lines\"], \"vibration\": {\"type\": \"vibration\", \"description\": \"vibrates\", \"vibration\": {\"vibration\": {\"type\": \"vibration\", \"vibration\": {\"vibration\": {\"type\": \"vibration\", \"vibration\": {\"vibration\": {\"type\": \"vibration\", \"vibration\": {\"vibration\": {\"type\": \"vibration\", \"vib"}, {"object": "wallet", "object_id": 1156, "gpt3_output": "\n\n{\"type\": \"wallet\", \"description\": \"black, with a red symbol\", \"similar objects\": [\"wallet\", \"keyboard\", \"notebook\"]}"}, {"object": "walrus", "object_id": 1157, "gpt3_output": "\n\n{\"type\": \" mammal \", \"description\": \"black, with a white fur; could have long beaks and a sharp beak, could be sheathed in a long tail\", \"similar objects\": [\"walrus\", \"seagull\", \"chicken\"]}"}, {"object": "wardrobe", "object_id": 1158, "gpt3_output": "\n\n{\"type\": \"clothes\", \"description\": \"round, simple design; could have a few details like buttons, straps, etc.\", \"similar objects\": [\"coat\", \"shower\", \"clotheshorse\", \"bunny\", \"turban\"]}"}, {"object": "washbasin", "object_id": 1159, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"zucchini\", \"description\": \" cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves \"\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "automatic_washer", "object_id": 1160, "gpt3_output": "\n\nThe feature that should focus on for an automatic washer is the control over how often the machine cleans and Warms the water. This control can help the user to make sure that the washer is used regularly and that the water is at a proper temperature."}, {"object": "watch", "object_id": 1161, "gpt3_output": "\n\nThe features that should be focus for an object detection model that smells zucchini should be the cylindrical shape, the smooth surface, and the green color. The model should be able to identify zucchini as a food item, but should not be able to identify the object itself."}, {"object": "water_bottle", "object_id": 1162, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"red; has a small hole in the top\", \"similar objects\": [\"sink\", \"fishing net\", \"water bottle\"]}"}, {"object": "water_cooler", "object_id": 1163, "gpt3_output": "\n\n{\"type\": \" UNHCR \", \"description\": \"A water cooler is a water bottle that is placed in a container of water and then poured over the top\", \"similar objects\": [\"faucet\", \" dispenser \", \" dispensing machine\"]}"}, {"object": "water_faucet", "object_id": 1164, "gpt3_output": "\n\n{\"type\": \"accessory\", \"description\": \"gray, with a handle and several screws at the top\", \"similar objects\": [\"faucet\", \"sink\", \"sinkable\" \n\n}"}, {"object": "water_heater", "object_id": 1165, "gpt3_output": "\n\n{\"type\": \"fuel\", \"description\": \"liquefied oil; could use gasoline or diesel\", \"similar objects\": [\"pump\", \"heater\", \"tank\", \"tank\", \"spill\", \"spill\", \"spill\", \"spill\", \"spill\", \"spill\", \"spill\", \"spill\", \"spill\", \"spill\", \"spill\", \"spill\", \"spill\", \"spill\", \"spill\", \"spill\", \"spill\", \"spill\", \"spill\", \"spill\", \"spill\", \"sp"}, {"object": "water_jug", "object_id": 1166, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "water_gun", "object_id": 1167, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for water plants is the model's ability to find water plants.\n\nInput:\n\nvegetable, Output:\n\nThe feature that should focus on for an object detection model that is looking for water plants is the model's ability to find water plants."}, {"object": "water_scooter", "object_id": 1168, "gpt3_output": "\n\n{\"type\": \"vehicle\", \"description\": \"green; has a water droplet on the front end\", \"similar objects\": [\"water bottle\", \"water dispenser\", \"fishing net\"]}"}, {"object": "water_ski", "object_id": 1169, "gpt3_output": "\n\n{\"type\": \"water\", \"price\": \"free\", \"description\": \"\", \"status\": \"available for purchase\", \"similar objects\": [\"snow\", \"ski\", \"water bottle\"]}"}, {"object": "water_tower", "object_id": 1170, "gpt3_output": "\n\n{\"type\": \"sign\", \"description\": \"\", \"type\": \"object\", \"position\": \"x\", \"type\": \"text\", \"size\": \"\", \"color\": \"\", \"altText\": \"No sign\""}, {"object": "watering_can", "object_id": 1171, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "watermelon", "object_id": 1172, "gpt3_output": "\n\n{\"type\": \"fruit\", \"description\": \"red, round, has a stem\", \"similar objects\": [\"apple\", \"banana\", \"pear\"]}"}, {"object": "weathervane", "object_id": 1173, "gpt3_output": "\n\nThe input should be a model that can detect different types of vegetables. The output should be a model that can detect different models."}, {"object": "webcam", "object_id": 1174, "gpt3_output": "\n\n{\"type\": \"digital camera\", \"description\": \"round, has a sensor\", \"similar objects\": [\"teacher's pet\", \"camera\"]}"}, {"object": "wedding_cake", "object_id": 1175, "gpt3_output": "\n\nThe object detection model should focus on finding objects with similar characteristics that are in a same place and with the same size. The model should also be able to identify different types of objects, such as vegetables and animals."}, {"object": "wedding_ring", "object_id": 1176, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for a zucchini should be the zucchini itself, not its size or shape."}, {"object": "wet_suit", "object_id": 1177, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"Wet Suit\", \"description\": \"A wet suit is a clothing item that is made to keep a person wet. It is a piece of clothing that is made to keep the user warm and protect them from the weather."}, {"object": "wheel", "object_id": 1178, "gpt3_output": "\n\n{\"type\": \"balloon\", \"description\": \"length; can be filled with water or food\", \"similar objects\": [\" balloon \", \" space shuttle \", \" space heater \", \" space station \"]"}, {"object": "wheelchair", "object_id": 1179, "gpt3_output": "\n\n{\"type\": \"chair\", \"description\": \"black, with a white cover\", \"similar objects\": [\"wheelchair\", \"bed\", \"trolley\"]"}, {"object": "whipped_cream", "object_id": 1180, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for food is its type. An object's type should be able to be determined from its features. For example, an animal's type could be determined by the type of fur that is on its fur, the type of skin that is on its skin, the type of fur on its fur, the type of skin on its skin, and the type of cream or paint that is on the object."}, {"object": "whistle", "object_id": 1181, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for clues about its surroundings is the object's size. object sizes can be used to help identify different objects, and help the model understand how big or small an object is. For example, an ambulance might be big enough to handle, but small enough to be seen with the eye."}, {"object": "wig", "object_id": 1182, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}, {"object": "wind_chime", "object_id": 1183, "gpt3_output": "\n\nThe feature of an object that should focus on for object detection models that are designed to detect objects is that they are designed to move. Object detection models that are designed to detect objects should be able to identify them as soon as they move."}, {"object": "windmill", "object_id": 1184, "gpt3_output": "\n\n{\"type\": \"mechanism\", \"description\": \"a physical object is being used as an input\", \"similar objects\": [\"pump\", \"faucet\", \"Refrigerator\"]"}, {"object": "window_box_(for_plants)", "object_id": 1185, "gpt3_output": "\n\nThe feature that should focus on for an input with a zucchini is its cylindrical shape. The feature that focuses on for an input with a red wok is its smooth surface. The feature that focuses on for an input with a ambulance is its red siren."}, {"object": "windshield_wiper", "object_id": 1186, "gpt3_output": "\n\nThe features that should be focus for an object detection model that smells zucchini should be the cylindrical shape, the smooth surface, and the green color. The model should be able to clean zucchini by using the wiper tool."}, {"object": "windsock", "object_id": 1187, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for zucchini is its size. This model should be able to identify zucchini as a food item.\n\nThe feature that should focus on for an object detection model that is looking for zucchini is its shape. This model should be able to identify zucchini as a food item."}, {"object": "wine_bottle", "object_id": 1188, "gpt3_output": "\n\n{\"type\": \"bottle\", \"name\": \"wine\", \"size\": \"small\", \"similar objects\": [\" bottle \", \" bottle \"]"}, {"object": "wine_bucket", "object_id": 1189, "gpt3_output": "\n\n{\"type\": \"item\", \"name\": \"Wine\", \"description\": \"Red; has a bubbly surface\", \"similar objects\": [\"wine\", \"flowers\"]}"}, {"object": "wineglass", "object_id": 1190, "gpt3_output": "\n\n{\"type\": \"bottle\", \"description\": \"red, with a straw\", \"similar objects\": [\"bottle\", \"coconut\", \"soda\"]}"}, {"object": "blinder_(for_horses)", "object_id": 1191, "gpt3_output": "\n\n{\"type\": \"image\", \"uuid\": \"cwc8jr8\", \"image_src\": \"https://www.biddenplanet.com/img/uploads/vegetables/zucchini/zucchini-image.jpg\", \"caption\": \"A zucchini (un)]\", \"contributing image\": \"https://www.biddenplanet.com/img/uploads/vegetables/zebra/zebra-image.jpg\", \"featured image\": \"https://www.biddenplanet.com/img/uploads/vegetables/apple/"}, {"object": "wok", "object_id": 1192, "gpt3_output": "\n\n{\"type\": \"cooking tool\", \"description\": \"round, deep, has a handle\", \"similar objects\": [\"pan\", \"pot\", \"frying pan\"]}"}, {"object": "wolf", "object_id": 1193, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black, white, or light-colored; could have a tail\", \"similar objects\": [\"wolf\", \"cat\", \"toucan\"]}"}, {"object": "wooden_spoon", "object_id": 1194, "gpt3_output": "\n\n{\"type\": \"ingredient\", \"description\": \"wooden spoon\", \"similar objects\": [\"pudding\", \"dessert\"]}"}, {"object": "wreath", "object_id": 1195, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for Vegetables is likely to be similar to the feature that is used for an object detection model that is looking for Animals."}, {"object": "wrench", "object_id": 1196, "gpt3_output": "\n\nThe feature that should focus on for an object detection model that is looking for solutions is finding and solving problems. This includes being able to identify the object, its type, and similar objects that it is solution to."}, {"object": "wristband", "object_id": 1197, "gpt3_output": "\n\n{\"type\": \"token\", \"description\": \"I have this token."}, {"object": "wristlet", "object_id": 1198, "gpt3_output": "\n\n{\"type\": \"object\", \"name\": \"wristlet\", \"description\": \"red; has a stem\", \"similar objects\": [\"watch\", \"bracelet\", \"bracelet card\"]}"}, {"object": "yacht", "object_id": 1199, "gpt3_output": "\n\n{\"type\": \"vessel\", \"description\": \"island, boat\", \"similar objects\": [\"ship\", \"car\", \"plane\"]}"}, {"object": "yogurt", "object_id": 1200, "gpt3_output": "\n\n{\"type\": \"dietary\", \"description\": \"vegetables; could have high fructose diet diet or a complex carbohydrate diet\", \"similar objects\": [\"banana\", \"frozen yogurt\", \"fruit\", \"berry\"]}"}, {"object": "yoke_(animal_equipment)", "object_id": 1201, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"black, smooth, has a long root; can be eaten\", \"similar objects\": [\"zucchini\", \"carrot\", \"sticker\", \"chopstick\"]}"}, {"object": "zebra", "object_id": 1202, "gpt3_output": "\n\n{\"type\": \"animal\", \"description\": \"black and white stripes; has a long mane\", \"similar objects\": [\"horse\", \"giraffe\", \"elephant\"]}"}, {"object": "zucchini", "object_id": 1203, "gpt3_output": "\n\n{\"type\": \"vegetable\", \"description\": \"cylindrical, green, smooth; could have brown and rough stems; could be sliced into round pieces; could has green leaves\", \"similar objects\": [\"cucumber\", \"eggplant\", \"green bean\"]}"}]