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These are not merely catchy sayings. Even though some sources may identify a phrase as a catchphrase, this list is for those that meet the definition given in the lead section of the catchphrase article and are notable for their widespread use within the culture. This list is distinct from the list of political catchphrases.
A similar phrase, "One Look Is Worth A Thousand Words", appears in a 1913 newspaper advertisement for the Piqua Auto Supply House of Piqua, Ohio. [4] Early use of the exact phrase appears in a 1918 newspaper advertisement for the San Antonio Light, which says: One of the Nation's Greatest Editors Says: One Picture is Worth a Thousand Words
A rebus (/ ˈ r iː b ə s / REE-bəss) is a puzzle device that combines the use of illustrated pictures with individual letters to depict words or phrases. For example: the word "been" might be depicted by a rebus showing an illustrated bumblebee next to a plus sign (+) and the letter "n".
A proverbial phrase or expression is a type of conventional saying similar to a proverb and transmitted by oral tradition. The difference is that a proverb is a fixed expression, while a proverbial phrase permits alterations to fit the grammar of the context. [1] [2] In 1768, John Ray defined a proverbial phrase as:
The Associated Press similarly reported Sgt. Kilroy's account of being hospitalized early in World War II, and his friend Sgt. James Maloney wrote the phrase on a bulletin board. Maloney continued to write the shortened phrase when he was shipped out a month later, according to the AP account, and other airmen soon picked it up.
A Crungus is an imaginary creature found in artificial intelligence text-to-image models, sometimes also referred to as a digital cryptid. Twitch streamer, voice actor, and comedian Guy Kelly found that typing the made-up word into the Craiyon image generator consistently produced pictures of a monstrous, hairy humanoid.
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This is achieved by first clustering similar sentences together using n-gram overlap. Recurring patterns are found within clusters by using multi-sequence alignment. Then the position of argument words is determined by finding areas of high variability within each cluster, aka between words shared by more than 50% of a cluster's sentences.