Describing Wordsfor Blips

examples: nosewinterblue eyeswoman

Here are some adjectives for blips: final, topmost, made-individual, single disruptive, weak but unmistakable, more fast-moving, fast incoming, red hostile, lonely pink, green fragmented, fourth green, impatient red, innocuous red, larger fragmented, foreign unidentified, small, fluorescent, sufficiently distinguishable, strangely impenetrable, indistinct, faraway, more, smaller, later twin, few greenish, large, amorphous, fast-moving red, clear-channel, lifeless green, little one-time, incoming green, single amber, substantial and solid, smaller, quicker. You can get the definitions of these blips adjectives by clicking on them. You might also like some words related to blips (and find more here).

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Click words for definitions.

Words to Describe blips

Below is a list of describing words for blips. 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 blips:

final, topmost made-individual single disruptive weak but unmistakable more fast-moving fast incoming red hostile lonely pink green fragmented fourth green impatient red innocuous red larger fragmented foreign unidentified small, fluorescent sufficiently distinguishable strangely impenetrable indistinct, faraway more, smaller later twin few greenish large, amorphous fast-moving red clear-channel lifeless green little one-time incoming green single amber
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substantial and solid smaller, quicker final weak tiny, fast-moving tiny, lone so-called phantom tiny fast-moving several intermittent bizarre evolutionary fidential many airborne insistent red telltale white large incoming lone red smaller purple tiny telltale again green little statistical single incoming small genetic strong steady small but unmistakable angry, red nondescript little circular white green phosphorescent fat, lumbering more insignificant little electronic quick blue single blue fluorescent blue green signal other unidentified occasional odd much sharper now solid minor little usual green single red same fantastic translational single green small dim few distant last green single sharp more red more green tiny brown fast-moving unidentified numerous white high white tiny bright large clear red and orange seemingly random ugly green tiny red new green statistical fluorescent large single many false compacted slow but steady large red inflationary unexplainable red-rimmed single large weirdest tiny little little bright disruptive bright-green gravitational few private amber several additional large blue fainter phosphorescent few tiny pear-shaped incoming new red secondary speedier red and green angry red insistent tell-tale several little telltale amorphous fragmented featureless inbound dark-blue infinitesimal faintest contraband electronic shapeless anomalous slow-moving puny eighth distinguishable unnoticed little green green and red red merest quicker erratic large green phantom frenetic sharper green unmistakable seismic outgoing outstanding extraneous impossible northernmost tiniest much smaller intermittent unidentifiable bright green digital instantaneous brief greenish stationary bright orange meteorological small green feeble topmost mid small red unexplained briefest idiotic blinking momentary orange little blue distant faint insignificant treble static rear transient steady colored discernible bright red weak single computerized sane unaccountable audio metallic dull brighter sporadic smaller small black funny runaway small white occasional condensed convincing airborne little red nonexistent substantial faraway ominous several small fleeting purple evolutionary hypnotic several more suspicious many other fragmentary slight unauthorized vagrant alert indistinct major noticeable one-time fourth bright joint fewer anonymous little white lumbering yellow impersonal minor false nearer emerald twin white fuzzy solitary impenetrable temporary odd random vast sparkling characteristic irritating blue solid multiple elusive genetic annoying glaring closer separate reddish spontaneous hostile crimson strange vague discreet angry distinct mere positive nameless double soviet clear final fat junior strong larger unexpected signal biggest frantic unusual particular extra individual dumb quick nearest innocent automatic sharp shadowy lone slightest harmless brown circular constant miserable fantastic next enormous central appropriate broad lesser gentle huge definite basic quiet monstrous alien personal actual hot dim unknown short pink additional active sudden large fresh tiny imperial slow interesting poor small mysterious golden familiar normal gray private numerous dark least more simple beautiful black long

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Words to Describe blips

As you've probably noticed, adjectives for "blips" are listed above. According to the algorithm that drives this website, the top 5 adjectives for "blips" are: final, topmost, made-individual, single disruptive, weak but unmistakable, and more fast-moving. There are 352 other words to describe blips listed above. Hopefully the above generated list of words to describe blips suits your needs.

If you're getting strange results, it may be that your query isn't quite in the right format. The search box should be a simple word or phrase, like "tiger" or "blue eyes". A search for words to describe "people who have blue eyes" will likely return zero results. So if you're not getting ideal results, check that your search term, "blips" isn't confusing the engine in this manner.

Note also that if there aren't many blips adjectives, or if there are none at all, it could be that your search term has an abiguous part-of-speech. For example, the word "blue" can be an noun and an adjective. This confuses the engine and so you might not get many adjectives describing it. I may look into fixing this in the future. You might also be wondering: What type of word is blips?

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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