Limitations of Tokenization
- Tokenization is unable to capture the meaning of the sentence hence, results in ambiguity.
- In certain languages like Chinese, Japanese, Arabic, lack distinct spaces between words. Hence, there is an absence of clear boundaries that complicates the process of tokenization.
- Text may also include more than one word, for example email address, URLs and special symbols, hence it is difficult to decide how to tokenize such elements.
NLP | How tokenizing text, sentence, words works
Tokenization in natural language processing (NLP) is a technique that involves dividing a sentence or phrase into smaller units known as tokens. These tokens can encompass words, dates, punctuation marks, or even fragments of words. The article aims to cover the fundamentals of tokenization, it’s types and use case.