level
int64 1
4
| level_id
stringclasses 4
values | category
stringlengths 1
60
| words
sequencelengths 4
4
|
---|---|---|---|
1 | π‘ | CRUSH INTO A COMPACT SHAPE | [
"BALL",
"CRUMPLE",
"SCRUNCH",
"WAD"
] |
2 | π’ | FASTENERS | [
"BUCKLE",
"CLIP",
"HOOK",
"SNAP"
] |
3 | π΅ | MARK AS COMPLETED | [
"CHECK",
"CROSS",
"STRIKE",
"TICK"
] |
4 | π£ | DEPICTED IN DALΓβS βTHE PERSISTENCE OF MEMORYβ | [
"ANT",
"BRANCH",
"CLOCK",
"MELTING"
] |
1 | π‘ | HARDLY BUSTLING | [
"CALM",
"QUIET",
"SLEEPY",
"SLOW"
] |
2 | π’ | EARN | [
"GROSS",
"MAKE",
"NET",
"YIELD"
] |
3 | π΅ | REMOTE CONTROL FUNCTIONS | [
"HOME",
"MUTE",
"STOP",
"VOLUME"
] |
4 | π£ | WORDS BEFORE βDRUMβ | [
"EAR",
"KETTLE",
"OIL",
"SNARE"
] |
1 | π‘ | CRUSH INTO A COMPACT SHAPE | [
"BALL",
"CRUMPLE",
"SCRUNCH",
"WAD"
] |
2 | π’ | FASTENERS | [
"BUCKLE",
"CLIP",
"HOOK",
"SNAP"
] |
3 | π΅ | MARK AS COMPLETED | [
"CHECK",
"CROSS",
"STRIKE",
"TICK"
] |
4 | π£ | DEPICTED IN DALΓβS βTHE PERSISTENCE OF MEMORYβ | [
"ANT",
"BRANCH",
"CLOCK",
"MELTING"
] |
1 | π‘ | PARTS OF A FOOT | [
"ARCH",
"BALL",
"HEEL",
"SOLE"
] |
2 | π’ | ONE DOLLAR | [
"BUCK",
"CLAM",
"SINGLE",
"SMACKER"
] |
3 | π΅ | KINDS OF MUSHROOMS | [
"BUTTON",
"MOREL",
"OYSTER",
"TRUMPET"
] |
4 | π£ | POT___ | [
"BELLY",
"HOLE",
"LUCK",
"STICKER"
] |
1 | π‘ | PERCEIVE | [
"CATCH",
"CLOCK",
"NOTICE",
"REGISTER"
] |
2 | π’ | CADENCE | [
"BEAT",
"METER",
"RHYTHM",
"TIME"
] |
3 | π΅ | ONE IN A GROUP OF TWELVE | [
"DONUT",
"INCH",
"JUROR",
"MONTH"
] |
4 | π£ | DOG ___ | [
"DAYS",
"PADDLE",
"TAG",
"TIRED"
] |
1 | π‘ | SLIMY ANIMALS | [
"EARTHWORM",
"EEL",
"SALAMANDER",
"SLUG"
] |
2 | π’ | THINGS THAT LUMINESCE | [
"AURORA",
"FIREFLY",
"GLOWSTICK",
"RADIUM"
] |
3 | π΅ | DUTCH SYMBOLS | [
"CANAL",
"CLOG",
"TULIP",
"WINDMILL"
] |
4 | π£ | ENDING WITH SYNONYMS FOR βPLUNGEβ | [
"GATECRASH",
"RAINDROP",
"SKYDIVE",
"WATERFALL"
] |
1 | π‘ | MOVE QUICKLY | [
"BOLT",
"DART",
"DASH",
"FLY"
] |
2 | π’ | FUN TIME | [
"BALL",
"BLAST",
"KICK",
"THRILL"
] |
3 | π΅ | WORDS BEFORE AN ADDRESSEE | [
"ATTENTION",
"DEAR",
"FOR",
"TO"
] |
4 | π£ | NAME ___ | [
"BRAND",
"DROP",
"GAME",
"NAMES"
] |
1 | π‘ | LUNCH ORDERS | [
"CLUB",
"HERO",
"MELT",
"WRAP"
] |
2 | π’ | USED TO MAKE COFFEE | [
"BEANS",
"FILTER",
"GRINDER",
"WATER"
] |
3 | π΅ | PAY, WITH βUPβ | [
"ANTE",
"COUGH",
"PONY",
"SETTLE"
] |
1 | π‘ | SHADES OF RED | [
"BRICK",
"CHERRY",
"MAROON",
"RUBY"
] |
2 | π’ | APPOINTMENT SPECIFICATIONS | [
"DATE",
"DURATION",
"LOCATION",
"TIME"
] |
3 | π΅ | DIFFERENT AMOUNTS OF HAIR | [
"HEAD",
"LOCK",
"STRAND",
"WISP"
] |
4 | π£ | TREE HOMOPHONES | [
"BEACH",
"FUR",
"PAIR",
"YOU"
] |
1 | π‘ | βNOTHING TO IT!β | [
"EASY",
"NO SWEAT",
"PIECE OF CAKE",
"SURE THING"
] |
2 | π’ | OBJECTS FROM GREEK MYTH | [
"AEGIS",
"APPLE OF DISCORD",
"GOLDEN FLEECE",
"PANDORAβS BOX"
] |
3 | π΅ | PROVERBIAL THINGS TO KICK | [
"CAN",
"HABIT",
"HORNETSβ NEST",
"TIRES"
] |
4 | π£ | STARTING WITH POSSESSIVE PRONOUNS | [
"HERSHEY",
"HISTAMINE",
"ITSY",
"MINEFIELD"
] |
1 | π‘ | BREAKFAST SIDES | [
"BACON",
"GRITS",
"HASH",
"TOAST"
] |
2 | π’ | PUSHES, AS A BUTTON | [
"CLICKS",
"HITS",
"PRESSES",
"TAPS"
] |
3 | π΅ | THEY HAVE A HORN | [
"AFRICA",
"BUGLER",
"CAR",
"UNICORN"
] |
4 | π£ | OSCAR-WINNING ACTORS | [
"BRIDGES",
"IRONS",
"PHOENIX",
"WASHINGTON"
] |
1 | π‘ | APPROXIMATELY | [
"ABOUT",
"AROUND",
"LIKE",
"ROUGHLY"
] |
2 | π’ | TREES | [
"ELDER",
"PALM",
"PINE",
"SPRUCE"
] |
3 | π΅ | SIZABLE, AS AN AMOUNT | [
"HANDSOME",
"HEALTHY",
"RESPECTABLE",
"TIDY"
] |
4 | π£ | U.S. STATE ABBREVIATIONS, PER AP STYLE GUIDE | [
"ALA",
"ARK",
"MISS",
"ORE"
] |
1 | π‘ | CELESTIAL OBJECTS | [
"COMET",
"MOON",
"PLANET",
"STAR"
] |
2 | π’ | ARCHERS | [
"CUPID",
"HAWKEYE",
"ROBIN HOOD",
"SAGITTARIUS"
] |
3 | π΅ | FEMALE ANIMALS | [
"JENNY",
"NANNY",
"QUEEN",
"VIXEN"
] |
4 | π£ | βS.N.L.β CAST MEMBERS | [
"FEY",
"RUDOLPH",
"SHANNON",
"STRONG"
] |
1 | π‘ | βLIONS AND TIGERS AND BEARS, OH MY!β | [
"BEARS",
"LIONS",
"OH MY",
"TIGERS"
] |
2 | π’ | BELOVED, AS A FRIEND | [
"CLOSE",
"DEAR",
"INTIMATE",
"TIGHT"
] |
3 | π΅ | WORDS THAT SOUND LIKE PLURAL LETTERS | [
"BEES",
"EASE",
"JAYS",
"USE"
] |
4 | π£ | WHEN TRIPLED, HIT SONG TITLES | [
"BILLS",
"BYE",
"GIMME",
"PLEASE"
] |
1 | π‘ | HOMOPHONES | [
"EWE",
"U",
"YEW",
"YOU"
] |
2 | π’ | NECKLINES | [
"BOAT",
"CREW",
"SCOOP",
"V"
] |
3 | π΅ | WAYS TO EXPRESS 1,000 | [
"GRAND",
"K",
"M",
"THOU"
] |
4 | π£ | SUPER ___ | [
"8",
"BOWL",
"GLUE",
"TUESDAY"
] |
1 | π‘ | SLANG FOR HEAD | [
"COCONUT",
"CROWN",
"DOME",
"SKULL"
] |
2 | π’ | PALINDROMES | [
"ABBA",
"KAYAK",
"NUN",
"STATS"
] |
3 | π΅ | POLICE PROCEDURALS | [
"BONES",
"ELEMENTARY",
"KOJAK",
"MONK"
] |
4 | π£ | FIRST IN A COMEDY DUO | [
"ABBOTT",
"FRY",
"KEY",
"LAUREL"
] |
1 | π‘ | LOOP | [
"BAND",
"CIRCLE",
"HOOP",
"RING"
] |
2 | π’ | COOKING VESSELS | [
"CASSEROLE",
"CROCK",
"PAN",
"POT"
] |
3 | π΅ | KINDS OF BEDS | [
"BUNK",
"CANOPY",
"MURPHY",
"SLEIGH"
] |
4 | π£ | THINGS CALLED βOSCARβ | [
"BALONEY",
"GROUCH",
"O",
"STATUETTE"
] |
1 | π‘ | CONCOCTION | [
"COCKTAIL",
"COMPOUND",
"MIXTURE",
"SOLUTION"
] |
2 | π’ | TYPES OF SENTENCES | [
"COMMAND",
"EXCLAMATION",
"QUESTION",
"STATEMENT"
] |
3 | π΅ | KINDS OF BROS | [
"CRYPTO",
"FINANCE",
"PHARMA",
"TECH"
] |
4 | π£ | COMPLAINT HOMOPHONES | [
"GROWN",
"MOWN",
"WHALE",
"WINE"
] |
1 | π‘ | DEFER | [
"DELAY",
"POSTPONE",
"SHELVE",
"TABLE"
] |
2 | π’ | BAR FIXTURES | [
"COUNTER",
"KEG",
"STOOL",
"TAP"
] |
3 | π΅ | WATERCRAFT | [
"BARGE",
"JUNK",
"SUB",
"TUG"
] |
4 | π£ | SEEN IN βDONKEY KONGβ | [
"BARREL",
"GORILLA",
"HAMMER",
"LADDER"
] |
1 | π‘ | DEAL WITH | [
"FIELD",
"HANDLE",
"MANAGE",
"TACKLE"
] |
2 | π’ | STYLES OF BEER | [
"BITTER",
"BOCK",
"SOUR",
"STOUT"
] |
3 | π΅ | INVESTMENT VERBS | [
"HEDGE",
"HOLD",
"SHORT",
"TRADE"
] |
4 | π£ | ___ DOME | [
"CAPITOL",
"CHROME",
"ONION",
"TEAPOT"
] |
1 | π‘ | INTREPIDITY | [
"GRIT",
"HEART",
"NERVE",
"PLUCK"
] |
2 | π’ | ROAD | [
"ARTERY",
"AVENUE",
"DRAG",
"DRIVE"
] |
3 | π΅ | KINDS OF PAPER | [
"CONSTRUCTION",
"GRAPH",
"TISSUE",
"WAX"
] |
4 | π£ | KINDS OF TENNIS COURTS | [
"CARPET",
"CLAY",
"GRASS",
"HARD"
] |
1 | π‘ | TYPES OF RADIO | [
"AM",
"HAM",
"SATELLITE",
"WALKIE-TALKIE"
] |
2 | π’ | KINDS OF PLAY FIGHTS | [
"FOOD",
"PILLOW",
"SNOWBALL",
"WATER BALLOON"
] |
3 | π΅ | SNACK CAKES | [
"DEVIL DOG",
"DING DONG",
"HOHO",
"YODEL"
] |
4 | π£ | CLASSIC JOKE STAPLES | [
"BAR",
"CHICKEN",
"KNOCK-KNOCK",
"LIGHT BULB"
] |
1 | π‘ | SPICES | [
"CLOVE",
"MACE",
"NUTMEG",
"PEPPER"
] |
2 | π’ | PERFORM POORLY | [
"FLAIL",
"FLOP",
"FLOUNDER",
"TANK"
] |
3 | π΅ | SKIM THROUGH, AS PAGES | [
"FLIP",
"LEAF",
"RIFFLE",
"THUMB"
] |
4 | π£ | POP SINGERS MINUS βSβ | [
"KEY",
"MAR",
"SPEAR",
"STYLE"
] |
1 | π‘ | FISH | [
"FLUKE",
"MULLET",
"SOLE",
"TANG"
] |
2 | π’ | WORDS IN AN AUCTION-ENDING PHRASE | [
"GOING",
"ONCE",
"SOLD",
"TWICE"
] |
3 | π΅ | GLOBAL CURRENCIES | [
"POUND",
"REAL",
"SOL",
"YUAN"
] |
4 | π£ | WORDS BEFORE βCUPβ | [
"BUTTER",
"DIVA",
"SOLO",
"WORLD"
] |
1 | π‘ | FANTASY CREATURES | [
"DRAGON",
"GIANT",
"PIXIE",
"TROLL"
] |
2 | π’ | EMAIL FOLDERS | [
"DRAFTS",
"SENT",
"SPAM",
"TRASH"
] |
3 | π΅ | CITRUS SODAS | [
"CRUSH",
"SPRITE",
"SQUIRT",
"STARRY"
] |
4 | π£ | ANIMAL HOMOPHONES | [
"BORE",
"LINKS",
"PHISH",
"TOWED"
] |
2 | π’ | OBJECTS WITH TEETH | [
"COMB",
"GEAR",
"SAW",
"ZIPPER"
] |
End of preview. Expand
in Dataset Viewer.
Made with the following script using a local copy of this website:
import re
from bs4 import BeautifulSoup
from datasets import Dataset
with open("Todayβs NYT Connections Answers Jan 5, #574 - Daily Updates & Hints - Word Tips.htm", encoding="utf-8") as f:
html = f.read()
soup = BeautifulSoup(html, "html.parser")
texts = re.findall(r'"([^"]*)"', "".join(soup.find_all("script")[9]))
texts = [" ".join(text.split()).replace(" ,", ", ") for text in texts if ":" in text and (text.startswith("π‘") or text.startswith("π’") or text.startswith("π΅") or text.startswith("π£"))]
levels = {
"π‘": 1,
"π’": 2,
"π΅": 3,
"π£": 4
}
def gen():
for group in texts:
level_id = group[:1]
group = group[2:]
category, group = group.split(":")
entry = {
"level": levels[level_id],
"level_id": level_id,
"category": category,
"words": [word.strip() for word in group.split(",")]
}
#pprint(entry)
yield entry
dataset = Dataset.from_generator(gen)
dataset.push_to_hub("T145/connections")
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