Package opennlp.tools.parser

Class ParserChunkerSequenceValidator

java.lang.Object

opennlp.tools.parser.ParserChunkerSequenceValidator

All Implemented Interfaces:

SequenceValidator<TokenTag>

public class ParserChunkerSequenceValidator
extends Object
implements SequenceValidator<TokenTag>

Constructor Summary

Constructors

Constructor	Description
ParserChunkerSequenceValidator(String[] outcomes)

Method Summary

Modifier and Type	Method	Description
boolean	validSequence(int i, String[] inputSequence, String[] tagList, String outcome)
boolean	validSequence(int i, TokenTag[] inputTuples, String[] outcomesSequence, String outcome)	Determines whether a particular continuation of a sequence is valid.

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

ParserChunkerSequenceValidator

public ParserChunkerSequenceValidator(String[] outcomes)

Method Detail

validSequence

public boolean validSequence(int i,
                             String[] inputSequence,
                             String[] tagList,
                             String outcome)

validSequence

public boolean validSequence(int i,
                             TokenTag[] inputTuples,
                             String[] outcomesSequence,
                             String outcome)

Description copied from interface: SequenceValidator

Determines whether a particular continuation of a sequence is valid. This is used to restrict invalid sequences such as those used in start/continue tag-based chunking or could be used to implement tag dictionary restrictions.

Specified by:

validSequence in interface SequenceValidator<TokenTag>

Parameters:

i - The index in the input sequence for which the new outcome is being proposed.

inputTuples - The input sequence.

outcomesSequence - The outcomes so far in this sequence.

outcome - The next proposed outcome for the outcomes sequence.

Returns:

true is the sequence would still be valid with the new outcome, false otherwise.