Describing Words

examples: nosewinterblue eyeswoman

This tool helps you find adjectives for things that you're trying to describe. Also check out ReverseDictionary.org and RelatedWords.org.

Click words for definitions.

Words to Describe t-shirt

Below is a list of describing words for t-shirt. You can sort the descriptive words by uniqueness or commonness using the button above. Sorry if there's a few unusual suggestions! The algorithm isn't perfect, but it does a pretty good job for most common nouns. Here's the list of words that can be used to describe t-shirt:

  • grubby sweat-soaked
  • disgustingly cold and clammy
  • disgustingly cold
  • baggy, grubby
  • voluminous long-sleeved
  • blindingly pink
  • oversize yellow
  • ancient striped
  • washed-out mercurial
  • crusty green
  • long-sleeved yellow
  • long, oversized
  • ragged, oversize
  • grubby red
  • long mauve
  • oversized pink
  • hopeful or wet
  • glamorous black
  • snug purple
  • single, unworn
  • clean pale-blue
  • red long-sleeved
  • long-sleeved, black
  • simple pink
  • international wet
  • pink health-club
  • clean health-club
  • now brown and white
  • oversize navy-blue
  • standard-issue gray
  • eye-stunningly red
  • snug long-sleeved
  • snug olive
  • turquoise oversized
  • tight decadent
  • still clean but wrinkled
  • baggy pastel
  • tight navy-blue
  • mostly shredded
  • humongous white
  • fresh long-sleeved
  • nicely tight
  • loose mauve
  • indescribably foul
  • ribbed white
  • mobile wet
  • black, sloppy
  • new magenta
  • wildly bright
  • gray three-button
  • green, oversized
  • oversize blue
  • sweaty gray
  • ratty white
  • cheery gray
  • white grimy
  • thin, long-sleeved
  • favorite well-worn
  • conservative brown
  • comfortable, practical
  • black long-sleeved
  • grubby yellow
  • tight, white
  • long-sleeved black
  • loose, purple
  • sloppy white
  • gray athletic
  • old, oversized
  • modestly long
  • long thermal
  • pink juicy
  • nearly threadbare
  • gaudy white
  • sloppy blue
  • skimpy green
  • casual black
  • tight white
  • baggy white
  • bloodstained white
  • big turquoise
  • old mauve
  • oversized orange
  • black, ribbed
  • casual red
  • functional white
  • decidedly feminist
  • newest black
  • health-club
  • white athletic
  • long-sleeved green
  • long-sleeved
  • oversized white
  • white, lacy
  • foul wet
  • snug white
  • now filthy
  • pristine black
  • sooty white
  • simple khaki
  • clean, gray

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Describing Words

The idea for the Describing Words engine came when I was building the engine for Related Words (it's like a thesaurus, but gives you a much broader set of related words, rather than just synonyms). While playing around with word vectors and the "HasProperty" API of conceptnet, I had a bit of fun trying to get the adjectives which commonly describe a word. Eventually I realised that there's a much better way of doing this: parse books!

Project Gutenberg was the initial corpus, but the parser got greedier and greedier and I ended up feeding it somewhere around 100 gigabytes of text files - mostly fiction, including many contemporary works. The parser simply looks through each book and pulls out the various descriptions of nouns.

Hopefully it's more than just a novelty and some people will actually find it useful for their writing and brainstorming, but one neat little thing to try is to compare two nouns which are similar, but different in some significant way - for example, gender is interesting: "woman" versus "man" and "boy" versus "girl". On an inital quick analysis it seems that authors of fiction are at least 4x more likely to describe women (as opposed to men) with beauty-related terms (regarding their weight, features and general attractiveness). In fact, "beautiful" is possibly the most widely used adjective for women in all of the world's literature, which is quite in line with the general unidimensional representation of women in many other media forms. If anyone wants to do further research into this, let me know and I can give you a lot more data (for example, there are about 25000 different entries for "woman" - too many to show here).

The blueness of the results represents their relative frequency. You can hover over an item for a second and the frequency score should pop up. The "uniqueness" sorting is default, and thanks to my Complicated Algorithm™, it orders them by the adjectives' uniqueness to that particular noun relative to other nouns (it's actually pretty simple). As you'd expect, you can click the "Sort By Usage Frequency" button to adjectives by their usage frequency for that noun.

Special thanks to the contributors of the open-source mongodb which was used in this project.

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