Package opennlp.tools.tokenize

# Interface Tokenizer

All Known Implementing Classes:
  `SimpleTokenizer`, `TokenizerME`, `WhitespaceTokenizer`, `WordpieceTokenizer`

public interface Tokenizer
The interface for tokenizers, which segment a string into its tokens.

Tokenization is a necessary step before more complex NLP tasks can be applied. These usually process text on a token level. The quality of tokenization is important because it influences the performance of high-level task applied to it.

In segmented languages like English most words are segmented by whitespaces expect for punctuations, etc. which is directly attached to the word without a white space in between, it is not possible to just split at all punctuations because in abbreviations dots are a part of the token itself. A `Tokenizer` is now responsible to split those tokens correctly.

In non-segmented languages like Chinese, tokenization is more difficult since words are not segmented by a whitespace.

Tokenizers can also be used to segment already identified tokens further into more atomic parts to get a deeper understanding. This approach helps more complex task to gain insight into tokens which do not represent words like numbers, units or tokens which are part of a special notation.

For most subsequent NLP tasks, it is desirable to over-tokenize rather than to under-tokenize.

- ## Method Summary

  Modifier and Type
  Method
  Description
  `String[]`
  `tokenize(String s)`
  Splits a string into its atomic parts.
  `Span[]`
  `tokenizePos(String s)`
  Finds the boundaries of atomic parts in a string.

- ## Method Details

  - ### tokenize

    String[] tokenize(String s)
    Splits a string into its atomic parts.
    Parameters:
      `s` - The string to be tokenized.
    Returns:
      The String[] with the individual tokens as the array elements.

  - ### tokenizePos

    Span[] tokenizePos(String s)
    Finds the boundaries of atomic parts in a string.
    Parameters:
      `s` - The string to be tokenized.
    Returns:
      The `spans (offsets into `s`)` for each token as the individuals array elements.