ContractionTokenizer.java

package edu.northwestern.at.utils.corpuslinguistics.tokenizer;

/*	Please see the license information at the end of this file. */

import java.util.*;
import edu.northwestern.at.utils.ListFactory;

/**	Split text containing contraction into separate tokens.
 */

public class ContractionTokenizer
	extends AbstractWordTokenizer
	implements WordTokenizer
{
	/**	Create a contraction tokenizer.
	 */

	public ContractionTokenizer()
	{
	}

	public static String prepareTextForTokenization( String str )
	{
		str = str.replaceAll("([^'])' ", "$1 ' ");
		str = str.replaceAll("'([sSmMdD]) ", " '$1 ");
		str = str.replaceAll("'ll ", " 'll ");
		str = str.replaceAll("'re ", " 're ");
		str = str.replaceAll("'ve ", " 've ");
		str = str.replaceAll("n't ", " n't ");
		str = str.replaceAll("'t ", " 't ");
		str = str.replaceAll("'s ", " 's ");
		str = str.replaceAll("'LL ", " 'LL ");
		str = str.replaceAll("'RE ", " 'RE ");
		str = str.replaceAll("'VE ", " 'VE ");
		str = str.replaceAll("N'T ", " N'T ");
		str = str.replaceAll("'T ", " 'T ");
		str = str.replaceAll("'S ", " 'S ");

		str = str.replaceAll(" ([Cc])annot ", " $1an not ");
		str = str.replaceAll(" ([Dd])'ye ", " $1' ye ");
		str = str.replaceAll(" ([Gg])imme ", " $1im me ");
		str = str.replaceAll(" ([Gg])onna ", " $1on na ");
		str = str.replaceAll(" ([Gg])otta ", " $1ot ta ");
		str = str.replaceAll(" ([Ll])emme ", " $1em me ");
		str = str.replaceAll(" ([Mm])ore'n ", " $1ore 'n ");
		str = str.replaceAll(" '([Tt])is ", " '$1 is ");
		str = str.replaceAll(" '([Tt])was ", " '$1 was ");
		str = str.replaceAll(" ([Ww])anna ", " $1an na ");

		str = str.trim();

		return str;
	}

	/**	Break text into word tokens.
	 *
	 *	@param	text			Text to break into word tokens.
	 *
	 *	@return					List of word tokens.
	 *
	 *	<p>
	 *	Word tokens may be words, numbers, punctuation, etc.
	 *	</p>
	 */

	 public List<String> extractWords( String text )
	 {
								//	Holds list of tokenized words.

	 	List<String> result	= ListFactory.createNewList();

	 							//	Prepare text for tokenization
	 							//	by splitting words and punctuation
	 							//	according to Penn Treebank rules.

	 	String fixedText	= prepareTextForTokenization( text );

	 							//	All we have to do now is pick
	 							//	up the individual "words" which
	 							//	are separated by one or more blanks.
	 							//	Use a StringTokenizer for this.

	 	StringTokenizer tokenizer	= new StringTokenizer( fixedText );

								//	Add each token to the results list.

		while ( tokenizer.hasMoreTokens() )
		{
			result.add( tokenizer.nextToken() );
		}
                    			//	Return tokenizer list of words.
		return result;
	}
}

/*
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Developed by:
   Academic and Research Technologies
   Northwestern University
   http://www.it.northwestern.edu/about/departments/at/

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obtaining a copy of this software and associated documentation
files (the "Software"), to deal with the Software without
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sell copies of the Software, and to permit persons to whom the
Software is furnished to do so, subject to the following
conditions:

    * Redistributions of source code must retain the above copyright
      notice, this list of conditions and the following disclaimers.

    * Redistributions in binary form must reproduce the above
      copyright notice, this list of conditions and the following
      disclaimers in the documentation and/or other materials provided
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      Northwestern University, nor the names of its contributors may be
      used to endorse or promote products derived from this Software
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