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.