Extract Unique Words

Create a list of distinct words or items from your text without changing the original input. The tool first collapses runs of whitespace to a single space, then finds unique tokens. Extracted items appear in the Extraction Panel where you can Copy to Clipboard, Paste to Editor (replace), or Append to Editor (add at the end).

How to use & Extraction Panel

1. Paste your text into the editor.
2. (Optional) Prepare tokens with helper tools — for example lowercase, remove punctuation, or remove non‑alphanumeric characters. The tool itself collapses whitespace but does not re-tokenize for you.
3. Select Extract → Unique words. The Extraction Panel will show the results.
4. Export or move the results:
   • Copy to Clipboard — quickly transfer results to other apps.
   • Paste to Editor (replace) — replace the editor content with the extracted list for further editing or export.
   • Append to Editor — add extracted items to the end of the current editor content (useful when merging lists).

What this tool does (short)

• Readonly operation: the original text remains unchanged unless you use Paste to Editor.
• Whitespace normalization: consecutive whitespace is collapsed to a single space before processing.
• Case behavior: by default the tool treats different cases as distinct (use Case Converter to normalize case first).
• Tokenization responsibility: the tool returns unique whitespace‑separated tokens after normalization — advanced token splitting (preserving hyphens, phrases, or CSV columns) should be done with helper tools first.

Extract Unique Items (EANs, SKUs, hashtags)

The same extractor works for non-word tokens if you prepare them correctly: e.g., turn comma lists into one item per line, strip formatting from identifiers, or remove punctuation around hashtags. This section documents quick workflows for item extraction.

Common use cases

• Hashtag lists: extract unique hashtags from social posts after running Remove Punctuation (or selectively strip surrounding characters).
• SKU / barcode lists: extract unique SKUs or codes after cleaning formatting with Remove Spaces or Remove Non‑Alphanumeric.
• Survey short answers: pull a unique set of short text answers for quick review or coding.
• Keyword discovery (readonly): collect distinct tokens from a seed document as a starting point for topic clustering — normalize with Case Converter and Remove Punctuation first.
• Data QA: spot unique IDs or stray tokens before importing to a database.

Examples (Input / Output)

Input (hashtags):

#summer #Sale #summer! #travel

Extracted:

#summer
#Sale
#summer!
#travel

Tip: run Remove Punctuation first to normalize trailing punctuation before extracting.

Input (SKUs, formatted):

SKU-1234, SKU 1234, sku-1234

Extracted:

SKU-1234
SKU 1234
sku-1234

Tip: run Remove Spaces and lowercase first to deduplicate variants.

Input (survey short answers):

fast delivery
great price
fast delivery
easy return policy

Extracted:

fast delivery
great price
easy return policy

When to use this vs Remove Duplicate Words

• Extract Unique Words — readonly extraction into the Extraction Panel. Use when you need a separate list of distinct tokens without modifying the source text.
• Remove Duplicate Words — in‑place editor operation that removes repeated tokens from your text. Use when you want the editor content cleaned directly.

Tool‑chaining & recommended workflows

• Case‑insensitive token list: lowercase → remove punctuation → extract unique words.
• SKU / EAN extraction: remove spaces → remove non‑alphanumeric characters → extract unique words.
• Preserve multiword phrases: convert comma lists to lines with Remove Line Breaks or manual editing, then run extract unique words.

Tips & edge cases

• The tool collapses whitespace to a single space but does not reformat tokens — handle tokenization (commas, hyphens, CSV columns) with helper tools before extraction.
• By default the tool is case‑sensitive — run Case Converter first if you want case‑insensitive results.
• For identifier lists (EAN/ISBN), strip separators and non‑digits with Remove Non‑Alphanumeric before extracting.
• Use Word Counter after extraction to get counts for the unique list if needed.