Deduplicate words with optional case-insensitive matching while keeping the first spelling encountered.
Audit word deduplication with original/unique counts, removed duplicates, stable order and case-sensitive comparison evidence.
The workflow compares source and output line count, blank lines, UTF-8 bytes, line-ending style and trailing-newline state. A no-op is reported explicitly instead of pretending text changed.
Use output as input only when the preview is what you intended. Restore returns to the page-load sample, and the before/after audit remains local to your browser.
Case sensitivity changes whether Word and word are duplicates. Punctuation, apostrophes, hyphens and Unicode variants can also affect token boundaries, so choose a normalization rule that matches the text you are cleaning.
For prose, tags, keyword lists and transcripts, keeping the first occurrence usually preserves the original flow better than sorting. If order is not meaningful, sort only after deduplication so the transformation remains easy to audit.
Record the original token count, unique token count and number removed. A surprisingly large reduction is a warning that the tokenizer or case rule may be collapsing items you intended to keep distinct.
Removing repeated words inside a text is different from removing repeated rows or lines. Use the transformation that matches the data unit, especially when working with CSV fields, addresses or multi-word labels.
If the cleaned text will feed another parser, generator or publishing step, inspect representative edge cases first. Quotes, contractions, emoji, non-Latin scripts and punctuation-heavy identifiers can behave differently from simple space-separated words.
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