Datasets:
bltlab
/
queryner

Dataset card Data Studio Files Community
2
tokens
sequencelengths
2
12
ner_tags
sequencelengths
2
12
[ "aquarium", "all", "in", "one" ]
[ 9, 17, 18, 18 ]
[ "tregar", "accessories" ]
[ 9, 10 ]
[ "bushnell", "ar", "15", "scope", "223" ]
[ 11, 25, 26, 26, 26 ]
[ "one", "day", "remains" ]
[ 7, 8, 8 ]
[ "dupont", "wire" ]
[ 11, 9 ]
[ "bluetooth", "mouse" ]
[ 17, 9 ]
[ "king", "platform", "bed", "without", "headboard" ]
[ 31, 9, 10, 31, 32 ]
[ "avent", "bottles" ]
[ 25, 9 ]
[ "oodji", "shirt", "dress" ]
[ 11, 9, 10 ]
[ "bungee", "cord" ]
[ 9, 10 ]
[ "personal", "care", "for", "women" ]
[ 9, 10, 13, 14 ]
[ "why", "nations", "fail" ]
[ 7, 8, 8 ]
[ "bar", "mat", "spill", "mat" ]
[ 9, 10, 10, 10 ]
[ "dance", "dresa" ]
[ 19, 9 ]
[ "earthquake", "kits", "for", "home" ]
[ 9, 10, 17, 18 ]
[ "ultra", "pro", "trading", "card", "storage", "box" ]
[ 11, 12, 17, 18, 9, 10 ]
[ "white", "chiffon", "high", "low", "dresses", "for", "women", "party", "wedding" ]
[ 3, 15, 31, 32, 9, 13, 14, 19, 19 ]
[ "wize", "gear" ]
[ 11, 12 ]
[ "husqvarna", "322l" ]
[ 11, 25 ]
[ "bandage", "dresses", "for", "women" ]
[ 9, 10, 13, 14 ]
[ "automatic", "toilet", "seat", "cover" ]
[ 17, 9, 10, 10 ]
[ "60", "x", "84", "oval", "tablecloth", "snowflake" ]
[ 1, 2, 2, 31, 9, 7 ]
[ "the", "sowers", "series" ]
[ 7, 8, 8 ]
[ "10.1", "inch", "tablet", "case", "without", "spen" ]
[ 1, 2, 9, 10, 5, 6 ]
[ "girls", "unicorn", "comforter", "sets", "twin" ]
[ 13, 7, 9, 10, 31 ]
[ "bcaa", "without", "artificial", "sweeteners" ]
[ 9, 5, 6, 6 ]
[ "pound", "blanket" ]
[ 0, 9 ]
[ "gates", "of", "fire" ]
[ 7, 8, 8 ]
[ "travelpro", "magna", "2" ]
[ 25, 26, 26 ]
[ "3/8", "in.", "od", "compression", "x", "3/8", "in.", "flare", "brass", "adapter", "fitting" ]
[ 1, 2, 17, 18, 0, 1, 2, 17, 15, 9, 10 ]
[ "spice", "rack", "cabinet" ]
[ 17, 9, 10 ]
[ "kids", "water", "play", "center" ]
[ 13, 9, 10, 10 ]
[ "girls", "wedding", "dress", "4-10", "years" ]
[ 13, 19, 9, 13, 14 ]
[ "good", "job", "stickers", "funny" ]
[ 7, 8, 9, 17 ]
[ "marian", "university", "indianapolis" ]
[ 7, 8, 8 ]
[ "lake", "launger" ]
[ 9, 10 ]
[ "table", "clock", "6-8", "inch" ]
[ 17, 9, 1, 2 ]
[ "water", "flavor", "packets" ]
[ 9, 10, 10 ]
[ "dji", "remote", "tablet", "holder", "pgytech" ]
[ 11, 9, 10, 10, 25 ]
[ "5", "year", "lined", "journal" ]
[ 13, 14, 17, 9 ]
[ "white", "snowflake", "ornaments" ]
[ 3, 31, 9 ]
[ "howard", "feed", "n", "wax", "wood", "polish", "and", "conditioner" ]
[ 11, 25, 26, 26, 9, 10, 10, 10 ]
[ "small", "kitchen", "table" ]
[ 1, 17, 9 ]
[ "cheap", "corsets", "for", "women" ]
[ 23, 9, 13, 14 ]
[ "canon", "mx492", "ink", "cartridges", "black" ]
[ 25, 26, 9, 10, 3 ]
[ "releev", "cold", "sore", "treatment" ]
[ 25, 9, 10, 10 ]
[ "naipo", "shiatsu", "back", "and", "neck", "massager", "with", "heat", "deep", "kneading" ]
[ 11, 17, 9, 10, 10, 10, 17, 18, 18, 18 ]
[ "fibits", "for", "kids" ]
[ 9, 13, 14 ]
[ "neon", "mesh", "cover", "up" ]
[ 3, 15, 9, 10 ]
[ "miller", "stick", "welder" ]
[ 11, 9, 10 ]
[ "law", "101", "everything", "you", "need", "about", "american", "law" ]
[ 7, 8, 8, 8, 8, 8, 8, 8 ]
[ "melatonin", "and", "valerian", "root" ]
[ 9, 10, 10, 10 ]
[ "mens", "t-shirts", "long" ]
[ 13, 9, 1 ]
[ "super", "you", "supplement" ]
[ 25, 26, 9 ]
[ "10", "kolinsky", "nail", "brush" ]
[ 1, 11, 9, 10 ]
[ "sink", "for", "kitchen" ]
[ 9, 17, 18 ]
[ "express", "womens", "clothing" ]
[ 11, 13, 9 ]
[ "nail", "cleanup", "brush" ]
[ 9, 10, 10 ]
[ "dried", "splitpeas" ]
[ 9, 10 ]
[ "wedding", "cake", "topper", "with", "3", "children" ]
[ 19, 9, 10, 17, 18, 18 ]
[ "gifts", "for", "7", "year", "old", "boy" ]
[ 9, 13, 14, 14, 14, 14 ]
[ "under", "armour", "volleyball", "spandex" ]
[ 11, 12, 9, 15 ]
[ "why", "does", "he", "do", "that", "lundy", "bancroft" ]
[ 7, 8, 8, 8, 8, 11, 12 ]
[ "bbq", "casual", "shirts", "for", "men" ]
[ 19, 17, 9, 13, 14 ]
[ "welcome", "to", "game" ]
[ 25, 26, 9 ]
[ "rugrats", "t", "shirt", "reptar" ]
[ 7, 9, 10, 7 ]
[ "computer", "without", "monitor" ]
[ 17, 5, 6 ]
[ "pillow", "for", "bathtub" ]
[ 9, 17, 18 ]
[ "9", "plus", "case" ]
[ 17, 18, 9 ]
[ "moroccan", "pants", "for", "women" ]
[ 17, 9, 13, 14 ]
[ "lexus", "is", "200t", "seat", "cover" ]
[ 17, 18, 18, 9, 10 ]
[ "ariel", "doll" ]
[ 7, 9 ]
[ "baby", "stroller", "without", "car", "seat" ]
[ 9, 10, 5, 6, 6 ]
[ "10mil", "syringe", "without", "needle" ]
[ 1, 9, 5, 6 ]
[ "areds", "2", "chewables" ]
[ 25, 26, 17 ]
[ "plus", "size", "orange", "leggings", "for", "women" ]
[ 1, 2, 3, 9, 13, 14 ]
[ "a70", "case" ]
[ 25, 9 ]
[ "happy", "notes" ]
[ 25, 26 ]
[ "gamer", "chair", "for", "kids" ]
[ 9, 10, 13, 14 ]
[ "recurve", "bow" ]
[ 9, 10 ]
[ "absolute", "new", "york", "brightening", "banana" ]
[ 11, 12, 12, 25, 26 ]
[ "clear", "handbag" ]
[ 17, 9 ]
[ "stick", "on", "towel", "holders", "for", "bathrooms" ]
[ 17, 18, 9, 10, 17, 18 ]
[ "gt", "plant", "based", "probiotic" ]
[ 11, 17, 18, 9 ]
[ "my", "little", "pony", "games" ]
[ 7, 8, 8, 9 ]
[ "mrcp", "part", "1" ]
[ 7, 8, 8 ]
[ "beautiful", "bedding" ]
[ 17, 9 ]
[ "statistical", "methods", "for", "engineers" ]
[ 7, 8, 8, 8 ]
[ "10", "oz", "plastic", "jars", "without", "lids", "bulk" ]
[ 1, 2, 15, 9, 5, 6, 6 ]
[ "accidental", "billionares" ]
[ 7, 8 ]
[ "hakuba", "matata", "gofts" ]
[ 7, 8, 9 ]
[ "men", "t", "shirts", "v", "neck", "cheap", "price" ]
[ 13, 9, 10, 31, 32, 23, 24 ]
[ "bodenov", "mask" ]
[ 9, 10 ]
[ "dump", "truck", "drivers", "gifts" ]
[ 13, 14, 14, 9 ]
[ "round", "rugs", "3", "feet" ]
[ 31, 9, 1, 2 ]
[ "wifi", "range", "extender" ]
[ 9, 10, 10 ]
[ "air", "fryer", "nuwave", "6", "qt" ]
[ 9, 10, 11, 1, 2 ]
[ "side", "shaper" ]
[ 9, 10 ]
[ "sexy", "lingerie", "sets", "for", "women", "plus", "size" ]
[ 17, 9, 10, 13, 14, 1, 2 ]
[ "one", "a", "day", "multivitamin", "for", "teens" ]
[ 11, 12, 12, 9, 13, 14 ]