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Word boundary folding

As explained in Natural Language Processing in Action, Second Edition

Word boundary folding normalizes punctuation and whitespace at word boundaries to one uniform character representation.

Word boundary folding gives punctuation and whitespace at word boundaries one uniform character representation. This keeps tokenization consistent when a search pipeline builds character trigrams. section 10.3.1

Consistent boundary trigrams

A trigram index for “trigram index” includes boundary trigrams such as “ tr” and “am ”. Folding every non-alpha boundary character to a space makes punctuation and whitespace produce comparable representations across documents. section 10.3.1

Use the folded representation while creating trigram indices and text vectors. Shared trigrams support approximate matching and more accurate relevance ranking, complementing or replacing stemming, lemmatization, and case folding in some search pipelines. section 10.3.1

How Natural Language Processing in Action, Second Edition covers it

How deep it goes
Defines the normalization rule and its ranking rationale, but does not provide implementation code or detailed index algorithms.
Examples
Uses “trigram index,” boundary trigrams, spaces, punctuation, and whitespace as concrete normalization examples.
What it assumes
Builds on character trigrams and tokenization, while relating the technique to the familiar idea of case folding.
What you can do after
Apply it during tokenization to improve approximate matching and relevance ranking in trigram-based search pipelines.
How it connects
Connects character trigrams with tokenization, case folding, stemming, lemmatization, and semantic search.

This explainer was generated by Manning's knowledge graph from the text of Natural Language Processing in Action, Second Edition. The section links point to the parts of the book it draws on.