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Upset can be an adjective, a noun or a verb.

upset used as an adjective:

  1. Of a person, angry, distressed or unhappy.

Adjectives are are describing words. An adjective is a word that modifies a noun or pronoun (examples: small, scary, silly). Adjectives make the meaning of a noun more precise. Learn more →

upset used as a noun:

  1. Disturbance or disruption.
    "My late arrival caused the professor considerable upset."
  2. (sports) An unexpected victory of a competitor that was not favored.
    "The Nimrods defeated the Blue Devils yesterday in a stunning upset."
  3. (automobile insurance) An overturn.
    ""collision and upset": impact with another object or an overturn for whatever reason."

Nouns are naming words. They are used to represent a person (soldier, Jamie), place (Germany, beach), thing (telephone, mirror), quality (hardness, courage), or an action (a run, a punch). Learn more →

upset used as a verb:

  1. To make (a person) angry, distressed, or unhappy.
    "I’m sure the bad news will upset him, but he needs to know."
  2. To disturb, disrupt or adversely alter (something).
    "Introducing a foreign species can upset the ecological balance."
  3. To tip or overturn (something).
  4. To defeat unexpectedly.
    "Truman upset Dewey in the 1948 US presidential election."

Verbs are action words and state of being words. Examples of action words are: ran, attacking, dreamed. Examples of "state of being" words are: is, was, be. Learn more →

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What type of word is upset?

As detailed above, 'upset' can be an adjective, a noun or a verb. Here are some examples of its usage:
  1. Noun usage: My late arrival caused the professor considerable upset.
  2. Noun usage: The Nimrods defeated the Blue Devils yesterday in a stunning upset.
  3. Noun usage: "collision and upset": impact with another object or an overturn for whatever reason.
  4. Verb usage: I’m sure the bad news will upset him, but he needs to know.
  5. Verb usage: Introducing a foreign species can upset the ecological balance.
  6. Verb usage: The fatty meat upset his stomach.
  7. Verb usage: Truman upset Dewey in the 1948 US presidential election.

Unfortunately, with the current database that runs this site, I don't have data about which senses of upset are used most commonly. I've got ideas about how to fix this but will need to find a source of "sense" frequencies. Hopefully there's enough info above to help you understand the part of speech of upset, and guess at its most common usage.

Word Type

For those interested in a little info about this site: it's a side project that I developed while working on Describing Words and Related Words. Both of those projects are based around words, but have much grander goals. I had an idea for a website that simply explains the word types of the words that you search for - just like a dictionary, but focussed on the part of speech of the words. And since I already had a lot of the infrastructure in place from the other two sites, I figured it wouldn't be too much more work to get this up and running.

The dictionary is based on the amazing Wiktionary project by wikimedia. I initially started with WordNet, but then realised that it was missing many types of words/lemma (determiners, pronouns, abbreviations, and many more). This caused me to investigate the 1913 edition of Websters Dictionary - which is now in the public domain. However, after a day's work wrangling it into a database I realised that there were far too many errors (especially with the part-of-speech tagging) for it to be viable for Word Type.

Finally, I went back to Wiktionary - which I already knew about, but had been avoiding because it's not properly structured for parsing. That's when I stumbled across the UBY project - an amazing project which needs more recognition. The researchers have parsed the whole of Wiktionary and other sources, and compiled everything into a single unified resource. I simply extracted the Wiktionary entries and threw them into this interface! So it took a little more work than expected, but I'm happy I kept at it after the first couple of blunders.

Special thanks to the contributors of the open-source code that was used in this project: the UBY project (mentioned above), @mongodb and express.js.

Currently, this is based on a version of wiktionary which is a few years old. I plan to update it to a newer version soon and that update should bring in a bunch of new word senses for many words (or more accurately, lemma).

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