ngram maker

Generates n-grams from input text to help writers, SEOs, and researchers identify common phrases and content opportunities.

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About This Tool

The Ngram Maker ingests plain text, normalizes case, and tokenizes into words. It slides a window of length n across tokens to generate all contiguous n-grams, then counts occurrences and applies optional filters such as minimum frequency and maximum results. Outputs are ordered by frequency or relevance, with support for overlapping sequences. This capability is essential for SEO content planning, linguistic research, and messaging refinement.
Advanced preprocessing options enable stopword removal, stemming or lemmatization, and locale-aware tokenization to focus on meaningful phrase patterns across languages. Users can run the tool on a single document or aggregate across multiple documents for corpus-wide insights; results are deterministic and suitable for reproducible reporting.
A typical workflow involves extracting top bigrams or trigrams from product descriptions, blog posts, or competitor pages to guide topic briefs, content gaps, and keyword strategy. Unique value lies in combining robust n-gram generation with flexible filtering and export options that fit downstream analytics.

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How to Use

Provide inputs: paste text, set n-gram length, and optional filters.
Choose preprocessing options: enable stopword removal or stemming if needed.
Run calculation: generate and sort n-grams by frequency.
Review outputs: examine top n-grams with counts and adjust max_results.
Export results: download JSON/CSV or copy for reports.

Frequently Asked Questions

Find Quick Answers

What is an n-gram?

An n-gram is a contiguous sequence of n tokens extracted from text. The tool analyzes word sequences to reveal common phrasing patterns and potential keyword opportunities, based on the chosen locale and tokenization rules.

What inputs are required?

You must provide the source text and the n-gram length (n). Optional inputs include min_freq, max_results, and locale. Defaults apply when optional fields are omitted.

Can I ignore stopwords or apply stemming?

Yes. The tool supports optional preprocessing to remove common stopwords and apply stemming or lemmatization, which helps focus on meaningful phrases and improves cross-language comparability.

How can I export the results?

Results can be exported as JSON or CSV, or copied into reports. This enables easy integration with downstream analytics and documentation workflows.

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