Real dictionary data, not a generated guess
Rather than generate a definition that could be subtly wrong, this looks up the word in a genuine English dictionary data source and returns its actual definitions, organized by part of speech, with example sentences and synonyms where available.
Why this tool doesn't actually use AI to generate anything
A language model asked to define a word can occasionally produce a definition that sounds confident but is subtly wrong, especially for words with multiple distinct meanings or fine shades of difference between close synonyms - looking the word up in an actual dictionary data source sidesteps that risk entirely, trading flexibility for reliability on something where getting it exactly right matters.
Why definitions are grouped by part of speech
Many words mean genuinely different things depending on whether they're used as a noun, verb, or adjective ("run" as a verb versus "a run" as a noun, for instance) - grouping definitions by part of speech first makes it immediately clear which meaning applies to how you're planning to use the word, rather than presenting an undifferentiated list that mixes unrelated senses together.
Why some words return no result
The dictionary source covers standard, established English vocabulary - very new slang, brand names, proper nouns, and genuine misspellings generally fall outside what any standard dictionary dataset covers, which is why those kinds of entries can come back empty even though the word itself might be perfectly understandable in context.