Datasets:
bltlab
/
queryner

Dataset card Data Studio Files Community
2
tokens
sequencelengths
2
12
ner_tags
sequencelengths
2
12
[ "velcro", "vegetables", "and", "fruit", "wood" ]
[ 9, 10, 10, 10, 15 ]
[ "womens", "purple", "slippers" ]
[ 13, 3, 9 ]
[ "lilou", "matte", "white", "spoon", "rest" ]
[ 25, 3, 4, 9, 10 ]
[ "writers", "reference" ]
[ 7, 8 ]
[ "linen", "textured", "curtains" ]
[ 15, 17, 9 ]
[ "mohair", "yarn" ]
[ 9, 10 ]
[ "batman", "pajamas", "for", "boys" ]
[ 7, 9, 13, 14 ]
[ "fishing", "chairs", "with", "rod", "holder" ]
[ 9, 10, 17, 18, 18 ]
[ "sweat", "bee", "traps", "outdoor" ]
[ 9, 10, 10, 17 ]
[ "p&s", "bead", "maker" ]
[ 11, 9, 10 ]
[ "epilator", "for", "women" ]
[ 9, 13, 14 ]
[ "sun", "seeds" ]
[ 9, 10 ]
[ "glitter", "gel", "markers", "for", "kids" ]
[ 17, 9, 10, 13, 14 ]
[ "usb", "to", "pc" ]
[ 9, 10, 10 ]
[ "patio", "bars" ]
[ 17, 9 ]
[ "white", "wedges" ]
[ 3, 9 ]
[ "faux", "orange", "garland" ]
[ 17, 15, 9 ]
[ "spy", "without", "a", "cause" ]
[ 7, 8, 8, 8 ]
[ "nautical", "womens", "clothing" ]
[ 17, 13, 9 ]
[ "postpartum", "leggings" ]
[ 17, 9 ]
[ "toddler", "finger", "paint" ]
[ 13, 17, 9 ]
[ "fgteev", "shirts", "for", "kids" ]
[ 7, 9, 13, 14 ]
[ "canon", "t7i", "camera" ]
[ 11, 25, 9 ]
[ "who", "not", "what", "book" ]
[ 0, 0, 0, 9 ]
[ "garmin", "vivofit", "band" ]
[ 11, 25, 9 ]
[ "dvb", "t2", "antenne" ]
[ 17, 18, 9 ]
[ "12", "oz", "hydroflask" ]
[ 1, 2, 11 ]
[ "gopro", "phone", "mount" ]
[ 25, 9, 10 ]
[ "disinfecting", "sprays" ]
[ 9, 10 ]
[ "felt", "flower" ]
[ 15, 9 ]
[ "giants", "football", "jearsy", "custum" ]
[ 7, 9, 10, 10 ]
[ "sony", "lens" ]
[ 11, 9 ]
[ "iphone", "charger", "6ft" ]
[ 25, 9, 1 ]
[ "floating", "wine", "glasses", "for", "the", "pool" ]
[ 17, 9, 10, 17, 18, 18 ]
[ "billard", "pool", "accessories" ]
[ 17, 18, 9 ]
[ "small", "baking", "dishes" ]
[ 1, 9, 10 ]
[ "melody", "susie", "nail", "drill", "bits" ]
[ 11, 12, 9, 10, 10 ]
[ "jojo", "siwa", "bows" ]
[ 7, 8, 9 ]
[ "booster", "vacuum", "hose" ]
[ 9, 10, 10 ]
[ "toys", "for", "2", "year", "old", "girls" ]
[ 9, 13, 14, 14, 14, 14 ]
[ "canvas", "tote", "bag", "kids" ]
[ 15, 9, 10, 13 ]
[ "cordless", "phones", "2", "handsets" ]
[ 9, 10, 17, 18 ]
[ "11", "cup", "rice", "cooker", "without", "warmer" ]
[ 1, 2, 9, 10, 5, 6 ]
[ "iphone", "7", "purse", "cases", "for", "women" ]
[ 25, 26, 31, 9, 13, 14 ]
[ "oil", "free", "face", "moisturizer" ]
[ 17, 18, 9, 10 ]
[ "yamaha", "guitar", "acoustic" ]
[ 11, 9, 17 ]
[ "waist", "trainer", "for", "women", "xs" ]
[ 9, 10, 13, 14, 1 ]
[ "bathroom", "trash", "can", "lif" ]
[ 17, 9, 10, 11 ]
[ "laundry", "room", "runner" ]
[ 17, 18, 9 ]
[ "decorations", "for", "teenagers", "rooms" ]
[ 9, 13, 14, 17 ]
[ "youth", "airsoft", "vest" ]
[ 13, 19, 9 ]
[ "jack", "reacher", "without", "fail" ]
[ 7, 8, 8, 8 ]
[ "iguana", "book" ]
[ 7, 9 ]
[ "aero", "chocolate" ]
[ 25, 9 ]
[ "rustic", "grey", "wall", "mirror" ]
[ 5, 3, 9, 10 ]
[ "outdoor", "sofa", "set" ]
[ 17, 9, 10 ]
[ "saltlife", "tank", "top", "shirts", "for", "men" ]
[ 11, 9, 10, 10, 13, 14 ]
[ "headphones", "with", "microphone" ]
[ 9, 17, 18 ]
[ "roller", "oils" ]
[ 9, 10 ]
[ "10m", "waterproof", "led", "strip", "lights", "outdoor", "without", "controller" ]
[ 17, 18, 9, 10, 10, 17, 5, 6 ]
[ "flat", "leather", "sandals", "for", "women" ]
[ 31, 15, 9, 13, 14 ]
[ "fish", "finder", "for", "shore", "fishing" ]
[ 9, 10, 19, 20, 20 ]
[ "mens", "clothing", "casual", "fashion" ]
[ 13, 9, 17, 18 ]
[ "solar", "headlamp" ]
[ 17, 9 ]
[ "slouchy", "moto", "boots", "for", "women" ]
[ 17, 9, 10, 13, 14 ]
[ "sully", "costume" ]
[ 7, 9 ]
[ "hair", "dye", "for", "dry", "scalp" ]
[ 9, 10, 17, 18, 18 ]
[ "home", "medical", "supplies", "and", "equipment", "for", "seniors" ]
[ 17, 9, 10, 10, 10, 13, 14 ]
[ "voltage", "converter" ]
[ 9, 10 ]
[ "72", "inch", "by", "72", "inch", "blinds" ]
[ 1, 2, 2, 2, 2, 9 ]
[ "refrigerator", "magnets", "for", "stainless", "steel", "fridge" ]
[ 17, 9, 17, 18, 18, 18 ]
[ "heart", "dog", "poop" ]
[ 25, 26, 26 ]
[ "leupold", "scope", "covers" ]
[ 11, 9, 10 ]
[ "photography", "poster" ]
[ 7, 9 ]
[ "ling", "ling", "potstickers" ]
[ 11, 12, 9 ]
[ "fresh", "fruit", "water", "dispenser" ]
[ 17, 18, 9, 10 ]
[ "hugo", "boss", "shirts", "for", "men" ]
[ 11, 12, 9, 13, 14 ]
[ "glucose", "tablets", "for", "low", "blood", "sugar" ]
[ 9, 10, 17, 18, 18, 18 ]
[ "bead", "necklace", "for", "women" ]
[ 15, 9, 13, 14 ]
[ "45", "women", "birthday", "party", "supplies" ]
[ 19, 13, 19, 9, 10 ]
[ "grey", "and", "white", "shower", "curtain" ]
[ 3, 0, 3, 9, 10 ]
[ "auto", "dash", "covers" ]
[ 17, 9, 10 ]
[ "little", "girl", "boots", "size", "11" ]
[ 13, 14, 9, 1, 2 ]
[ "micro", "fairy", "lights" ]
[ 31, 9, 10 ]
[ "whiskey", "stones" ]
[ 9, 10 ]
[ "thule", "electronics", "organizer" ]
[ 11, 17, 9 ]
[ "10x", "13", "picture", "without", "the", "frame" ]
[ 1, 2, 9, 5, 6, 6 ]
[ "car", "amp", "and", "sub" ]
[ 17, 9, 10, 10 ]
[ "simply", "better", "tea" ]
[ 25, 26, 26 ]
[ "sexy", "cat", "girl", "figures" ]
[ 17, 7, 8, 9 ]
[ "chocolate", "filled", "straws" ]
[ 9, 10, 10 ]
[ "ken", "kaneki" ]
[ 7, 8 ]
[ "frozen", "hoodie", "blanket" ]
[ 7, 9, 10 ]
[ "mens", "ultraboost", "adidas" ]
[ 13, 25, 11 ]
[ "asus", "x570" ]
[ 11, 27 ]
[ "michael", "kors", "shoes", "for", "women", "heels" ]
[ 11, 12, 9, 13, 14, 9 ]
[ "elvish", "wedding" ]
[ 17, 19 ]
[ "printable", "ecard", "gift", "card" ]
[ 17, 18, 9, 10 ]
[ "sink", "grid", "12x15" ]
[ 9, 10, 1 ]
[ "placemat", "cotton", "linen" ]
[ 9, 15, 15 ]