N-Gram Generator
Create word and character n-grams with adjustable length, casing, punctuation, and frequency output.
Result
Related tools
All Word Games ->How N-Gram Generator works
An n-gram is a continuous sequence of items from text. In word-based analysis, a 1-gram is one word, a 2-gram is a two-word phrase, and a 3-gram is a three-word phrase. In character-based analysis, n-grams are sequences of letters or characters instead of whole words.
Use this n-gram generator to find repeated phrases, inspect language patterns, prepare lightweight NLP features, compare text samples, or explore how words commonly appear together. It can generate word n-grams for phrase analysis or character n-grams for lower-level text patterns.
N-grams are used in natural language processing, search, autocomplete, spelling correction, text classification, authorship analysis, SEO research, and keyword discovery. For example, repeated 2-grams can show common phrases, while repeated 3-grams can reveal longer topic patterns.
For content and SEO work, n-grams can surface phrase-level repetition that a simple keyword counter misses. For technical analysis, character n-grams can help with fuzzy matching, language identification, and comparing strings that may contain spelling variations.
Choose a small n value when you want broad patterns and a larger n value when you want more specific phrases. Very large n-grams are usually sparse unless the source text is long or repetitive.
FAQ
What is an n-gram?
An n-gram is a continuous sequence of n words or characters. A 2-gram has two items, and a 3-gram has three.
What are n-grams used for?
N-grams are used for phrase analysis, autocomplete, search, spelling correction, text classification, language detection, SEO research, and other NLP tasks.
Should I use word n-grams or character n-grams?
Use word n-grams to analyze phrases and repeated wording. Use character n-grams for string patterns, fuzzy matching, spelling variation, or language-level analysis.
What n-gram size should I choose?
Start with 2 for common phrase pairs or 3 for longer phrase patterns. Larger n values are more specific and usually need more source text.