From Text to Token: How Tokenization Pipelines Work
Summary
The article walks through a tokenization pipeline for search systems, illustrating how text is filtered, split into tokens, stopwords removed, and stemming applied to produce indexable tokens. It compares tokenizers (word, partial, structured) and notes trade-offs like over-stemming and the role of stopwords. It also emphasizes tokenization as foundational for search accuracy and shows practical examples with a test sentence.