Word vs subword tokenization?

Word tokenization splits on whitespace — simple but produces a large vocabulary and cannot handle unknown words. Subword tokenization (BPE, WordPiece) splits words into common subword units (e.g., "playing" → "play" + "ing") — smaller vocabulary, handles unknown words. LLMs use subword tokenization.

How do I handle punctuation in tokenization?

For word tokenization, decide whether punctuation is a separate token or attached to the word. "Hello, world!" → ["Hello", ",", "world", "!"] (separate) or ["Hello,", "world!"] (attached). For NLP, separate tokens are standard. Use regex or an NLP library for consistent handling.

TASK

Tokenize text for NLP processing

Tokenization splits text into tokens (words, sentences, subwords). Learn word, sentence, and subword tokenization for NLP tasks.

1

Tokenization splits text into units for processing. Word tokenization splits on whitespace and punctuation. Sentence tokenization splits on sentence boundaries (. ! ?). Subword tokenization (BPE, WordPiece) splits rare words into common subwords — used by LLMs. The choice depends on the NLP task.
2

Word Count →
Count words and get basic word statistics. This gives a rough tokenization by splitting on whitespace. For more accurate tokenization, handle punctuation (don't split "don't" into "don" and "t"), contractions, and hyphenated words.
3

Regex Tester →
Use regex for word tokenization: \b\w+\b matches word boundaries. For sentence tokenization: [^.!?]+[.!?] splits on sentence-ending punctuation. For more accurate tokenization, use an NLP library (NLTK, spaCy) that handles edge cases (abbreviations, ellipses, quotes).

Frequently asked questions

Word vs subword tokenization?: Word tokenization splits on whitespace — simple but produces a large vocabulary and cannot handle unknown words. Subword tokenization (BPE, WordPiece) splits words into common subword units (e.g., "playing" → "play" + "ing") — smaller vocabulary, handles unknown words. LLMs use subword tokenization.
How do I handle punctuation in tokenization?: For word tokenization, decide whether punctuation is a separate token or attached to the word. "Hello, world!" → ["Hello", ",", "world", "!"] (separate) or ["Hello,", "world!"] (attached). For NLP, separate tokens are standard. Use regex or an NLP library for consistent handling.