opennlp-similarity/src/test/java/opennlp/tools/textsimilarity/chunker2matcher/ParserChunker2MatcherProcessorTest.java - opennlp-sandbox - Git at Google

 /*

  * Licensed to the Apache Software Foundation (ASF) under one or more
  * contributor license agreements.  See the NOTICE file distributed with
  * this work for additional information regarding copyright ownership.
  * The ASF licenses this file to You under the Apache License, Version 2.0
  * (the "License"); you may not use this file except in compliance with
  * the License. You may obtain a copy of the License at
  *
  *     http://www.apache.org/licenses/LICENSE-2.0
  *
  * Unless required by applicable law or agreed to in writing, software
  * distributed under the License is distributed on an "AS IS" BASIS,
  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
 package opennlp.tools.textsimilarity.chunker2matcher;

 import java.util.List;

 import junit.framework.TestCase;

 import opennlp.tools.textsimilarity.ParseTreeChunk;
 import opennlp.tools.textsimilarity.ParseTreeChunkListScorer;
 import opennlp.tools.textsimilarity.TextSimilarityBagOfWords;

 public class ParserChunker2MatcherProcessorTest extends TestCase {
   private ParserChunker2MatcherProcessor parser;
   private TextSimilarityBagOfWords parserBOW = new TextSimilarityBagOfWords();
   private ParseTreeChunkListScorer parseTreeChunkListScorer = new ParseTreeChunkListScorer();

   public void testGroupedPhrasesFormer() {
     parser = ParserChunker2MatcherProcessor.getInstance();
     String text = "Where do I apply? Go to your town office or city hall. If your town doesn't have an office, ask the town clerk or a Selectman. Tell them that you need a 1040 tax form . I Can 't Pay the Taxes on my House: What Can I Do?. Pine Tree Legal";

     List<List<ParseTreeChunk>> res = parser
         .formGroupedPhrasesFromChunksForPara(text);
     System.out.println(res);
     assertEquals(
         "[[NP [PRP$-your NN-town NN-office CC-or NN-city NN-hall ], NP [PRP$-your NN-town NN-doesn NN-t ], NP [DT-an NN-office ], NP [DT-the NN-town NN-clerk CC-or DT-a NNP-Selectman ], NP [DT-a NNP-Selectman ], NP [PRP-them IN-that PRP-you ], NP [PRP-you ], NP [DT-a CD-1040 NN-tax NN-form ], NP [PRP-I ], NP [DT-the NNS-Taxes IN-on PRP$-my NNP-House WP-What MD-Can PRP-I ], NP [PRP$-my NNP-House WP-What MD-Can PRP-I ], NP [WP-What MD-Can PRP-I ], NP [PRP-I ], NP [NNP-Pine NNP-Tree NNP-Legal ]], [VP [VBP-do RB-I VB-apply ], VP [VB-Go TO-to PRP$-your NN-town NN-office CC-or NN-city NN-hall ], VP [VBP-have DT-an NN-office ], VP [VB-ask DT-the NN-town NN-clerk CC-or DT-a NNP-Selectman ], VP [VB-Tell PRP-them IN-that PRP-you ], VP [VBP-need DT-a CD-1040 NN-tax NN-form ], VP [MD-Can VB-t VB-Pay DT-the NNS-Taxes IN-on PRP$-my NNP-House WP-What MD-Can PRP-I ], VP [VB-Do ]], [PP [TO-to PRP$-your NN-town NN-office CC-or NN-city NN-hall ], PP [IN-on PRP$-my NNP-House WP-What MD-Can PRP-I ]], [], [SENTENCE [WRB-Where VBP-do RB-I VB-apply ], SENTENCE [VB-Go TO-to PRP$-your NN-town NN-office CC-or NN-city NN-hall ], SENTENCE [IN-If PRP$-your NN-town NN-doesn NN-t VBP-have DT-an NN-office VB-ask DT-the NN-town NN-clerk CC-or DT-a NNP-Selectman ], SENTENCE [VB-Tell PRP-them IN-that PRP-you VBP-need DT-a CD-1040 NN-tax NN-form ], SENTENCE [PRP-I MD-Can VB-t VB-Pay DT-the NNS-Taxes IN-on PRP$-my NNP-House WP-What MD-Can PRP-I VB-Do ], SENTENCE [NNP-Pine NNP-Tree NNP-Legal ]]]",
         // "[[NP [PRP$-your NN-town NN-office CC-or NN-city NN-hall ], NP [PRP$-your NN-town NN-doesn NN-t ], NP [DT-an NN-office ], NP [DT-the NN-town NN-clerk CC-or DT-a NNP-Selectman ], NP [DT-a NNP-Selectman ], NP [PRP-them IN-that PRP-you ], NP [PRP-you ], NP [DT-a CD-1040 NN-tax NN-form ], NP [PRP-I ], NP [DT-the NNS-Taxes IN-on PRP$-my NNP-House WP-What MD-Can PRP-I ], NP [PRP$-my NNP-House WP-What MD-Can PRP-I ], NP [WP-What MD-Can PRP-I ], NP [PRP-I ], NP [NNP-Pine NNP-Tree NNP-Legal ]], [VP [VBP-do RB-I VB-apply ], VP [VB-Go TO-to PRP$-your NN-town NN-office CC-or NN-city NN-hall ], VP [VBP-have DT-an NN-office ], VP [VB-ask DT-the NN-town NN-clerk CC-or DT-a NNP-Selectman ], VP [VB-Tell PRP-them IN-that PRP-you ], VP [VBP-need DT-a CD-1040 NN-tax NN-form ], VP [MD-Can VB-t VB-Pay DT-the NNS-Taxes IN-on PRP$-my NNP-House WP-What MD-Can PRP-I ], VP [VB-Do NNP-Pine NNP-Tree NNP-Legal ]], [PP [TO-to PRP$-your NN-town NN-office CC-or NN-city NN-hall ], PP [IN-on PRP$-my NNP-House WP-What MD-Can PRP-I ]], [], [SENTENCE [WRB-Where VBP-do RB-I VB-apply ], SENTENCE [VB-Go TO-to PRP$-your NN-town NN-office CC-or NN-city NN-hall ], SENTENCE [IN-If PRP$-your NN-town NN-doesn NN-t VBP-have DT-an NN-office VB-ask DT-the NN-town NN-clerk CC-or DT-a NNP-Selectman ], SENTENCE [VB-Tell PRP-them IN-that PRP-you VBP-need DT-a CD-1040 NN-tax NN-form ], SENTENCE [PRP-I MD-Can VB-t VB-Pay DT-the NNS-Taxes IN-on PRP$-my NNP-House WP-What MD-Can PRP-I VB-Do NNP-Pine NNP-Tree NNP-Legal ]]]",
         res.toString());

     res = parser
         .formGroupedPhrasesFromChunksForSentence("How can I get short focus zoom lens for digital camera");
     assertEquals(
         "[[NP [PRP-I ], NP [JJ-short NN-focus NN-zoom NN-lens IN-for JJ-digital NN-camera ], NP [JJ-digital NN-camera ]], [VP [VB-get JJ-short NN-focus NN-zoom NN-lens IN-for JJ-digital NN-camera ]], [PP [IN-for JJ-digital NN-camera ]], [], [SENTENCE [WRB-How MD-can PRP-I VB-get JJ-short NN-focus NN-zoom NN-lens IN-for JJ-digital NN-camera ]]]",
         res.toString());

     res = parser
         .formGroupedPhrasesFromChunksForSentence("Its classy design and the Mercedes name make it a very cool vehicle to drive. ");
     assertEquals(
         "[[NP [PRP$-Its JJ-classy NN-design CC-and DT-the NNP-Mercedes NN-name ], NP [DT-the NNP-Mercedes NN-name ], NP [PRP-it DT-a RB-very JJ-cool NN-vehicle TO-to NN-drive ], NP [DT-a RB-very JJ-cool NN-vehicle TO-to NN-drive ], NP [NN-drive ]], [VP [VBP-make PRP-it DT-a RB-very JJ-cool NN-vehicle TO-to NN-drive ]], [PP [TO-to NN-drive ]], [], [SENTENCE [PRP$-Its JJ-classy NN-design CC-and DT-the NNP-Mercedes NN-name VBP-make PRP-it DT-a RB-very JJ-cool NN-vehicle TO-to NN-drive ]]]",
         res.toString());
     res = parser
         .formGroupedPhrasesFromChunksForSentence("Sounds too good to be true but it actually is, the world's first flying car is finally here. ");
     assertEquals(
         "[[NP [PRP-it RB-actually ], NP [DT-the NN-world NNS-s JJ-first NN-flying NN-car ]], [VP [VBZ-Sounds RB-too JJ-good ], VP [TO-to VB-be JJ-true CC-but PRP-it RB-actually ], VP [VBZ-is DT-the NN-world NNS-s JJ-first NN-flying NN-car ], VP [VBZ-is RB-finally RB-here ]], [], [ADJP [RB-too JJ-good ], ADJP [JJ-true CC-but PRP-it RB-actually ]], [SENTENCE [VBZ-Sounds RB-too JJ-good TO-to VB-be JJ-true CC-but PRP-it RB-actually VBZ-is DT-the NN-world NNS-s JJ-first NN-flying NN-car VBZ-is RB-finally RB-here ]]]",
         res.toString());
     res = parser
         .formGroupedPhrasesFromChunksForSentence("UN Ambassador Ron Prosor repeated the Israeli position that the only way the Palestinians will get UN membership and statehood is through direct negotiations with the Israelis on a comprehensive peace agreement");
     assertEquals(
         "[[NP [NNP-UN NNP-Ambassador NNP-Ron NNP-Prosor ], NP [DT-the JJ-Israeli NN-position IN-that DT-the JJ-only NN-way DT-the NNPS-Palestinians ], NP [DT-the JJ-only NN-way DT-the NNPS-Palestinians ], NP [DT-the NNPS-Palestinians ], NP [NN-membership CC-and NN-statehood VBZ-is IN-through JJ-direct NNS-negotiations IN-with DT-the NNP-Israelis IN-on DT-a JJ-comprehensive NN-peace NN-agreement ], NP [JJ-direct NNS-negotiations IN-with DT-the NNP-Israelis IN-on DT-a JJ-comprehensive NN-peace NN-agreement ], NP [DT-the NNP-Israelis IN-on DT-a JJ-comprehensive NN-peace NN-agreement ], NP [DT-a JJ-comprehensive NN-peace NN-agreement ]], [VP [VBD-repeated DT-the JJ-Israeli NN-position IN-that DT-the JJ-only NN-way DT-the NNPS-Palestinians ], VP [MD-will VB-get IN-UN NN-membership CC-and NN-statehood VBZ-is IN-through JJ-direct NNS-negotiations IN-with DT-the NNP-Israelis IN-on DT-a JJ-comprehensive NN-peace NN-agreement ]], [PP [IN-that DT-the JJ-only NN-way DT-the NNPS-Palestinians ], PP [IN-UN NN-membership CC-and NN-statehood VBZ-is IN-through JJ-direct NNS-negotiations IN-with DT-the NNP-Israelis IN-on DT-a JJ-comprehensive NN-peace NN-agreement ], PP [IN-through JJ-direct NNS-negotiations IN-with DT-the NNP-Israelis IN-on DT-a JJ-comprehensive NN-peace NN-agreement ], PP [IN-with DT-the NNP-Israelis IN-on DT-a JJ-comprehensive NN-peace NN-agreement ], PP [IN-on DT-a JJ-comprehensive NN-peace NN-agreement ]], [], [SENTENCE [NNP-UN NNP-Ambassador NNP-Ron NNP-Prosor VBD-repeated DT-the JJ-Israeli NN-position IN-that DT-the JJ-only NN-way DT-the NNPS-Palestinians MD-will VB-get IN-UN NN-membership CC-and NN-statehood VBZ-is IN-through JJ-direct NNS-negotiations IN-with DT-the NNP-Israelis IN-on DT-a JJ-comprehensive NN-peace NN-agreement ]]]",
         res.toString());
     parser.close();
   }

   public void testPrintParseTree() {
     parser = ParserChunker2MatcherProcessor.getInstance();
     try {
       parser
           .printParseTree("How can I get short focus zoom lens for digital camera");
     } catch (Exception e) {
       // when models does not read
     }
     parser.close();
   }

   public void testRelevanceAssessm() {
     parser = ParserChunker2MatcherProcessor.getInstance();
     String phrase1 = "Its classy design and the Mercedes name make it a very cool vehicle to drive. "
         + "The engine makes it a powerful car. "
         + "The strong engine gives it enough power. "
         + "The strong engine gives the car a lot of power.";
     String phrase2 = "This car has a great engine. "
         + "This car has an amazingly good engine. "
         + "This car provides you a very good mileage.";

     System.out.println(parser.assessRelevance(phrase1, phrase2)
         .getMatchResult());
     parser.close();

   }

   public void testCompareRelevanceAssessmWithBagOfWords() {
     parser = ParserChunker2MatcherProcessor.getInstance();
     // we first demonstrate how similarity expression for DIFFERENT cases have
     // too high score for bagOfWords
     String phrase1 = "How to deduct rental expense from income ";
     String phrase2 = "How to deduct repair expense from rental income.";
     List<List<ParseTreeChunk>> matchResult = parser.assessRelevance(phrase1,
         phrase2).getMatchResult();
     assertEquals(
         "[[ [NN-expense IN-from NN-income ],  [JJ-rental NN-* ]], [ [TO-to VB-deduct JJ-rental NN-* ],  [VB-deduct NN-expense IN-from NN-income ]]]",
         matchResult.toString());
     System.out.println(matchResult);
     double matchScore = parseTreeChunkListScorer
         .getParseTreeChunkListScore(matchResult);
     double bagOfWordsScore = parserBOW.assessRelevanceAndGetScore(phrase1,
         phrase2);
     assertTrue(matchScore + 2 < bagOfWordsScore);
     System.out.println("MatchScore is adequate ( = " + matchScore
         + ") and bagOfWordsScore = " + bagOfWordsScore + " is too high");

     // we now demonstrate how similarity can be captured by POS and cannot be
     // captured by bagOfWords
     phrase1 = "Way to minimize medical expense for my daughter";
     phrase2 = "Means to deduct educational expense for my son";
     matchResult = parser.assessRelevance(phrase1, phrase2).getMatchResult();
     assertEquals(
         "[[ [JJ-* NN-expense IN-for PRP$-my NN-* ]], [ [TO-to VB-* JJ-* NN-expense IN-for PRP$-my NN-* ]]]",
         matchResult.toString());
     System.out.println(matchResult);
     matchScore = parseTreeChunkListScorer
         .getParseTreeChunkListScore(matchResult);
     bagOfWordsScore = parserBOW.assessRelevanceAndGetScore(phrase1, phrase2);
     assertTrue(matchScore > 2 * bagOfWordsScore);
     System.out.println("MatchScore is adequate ( = " + matchScore
         + ") and bagOfWordsScore = " + bagOfWordsScore + " is too low");
     parser.close();

   }
 }
	/*

	* Licensed to the Apache Software Foundation (ASF) under one or more
	* contributor license agreements. See the NOTICE file distributed with
	* this work for additional information regarding copyright ownership.
	* The ASF licenses this file to You under the Apache License, Version 2.0
	* (the "License"); you may not use this file except in compliance with
	* the License. You may obtain a copy of the License at
	*
	* http://www.apache.org/licenses/LICENSE-2.0
	*
	* Unless required by applicable law or agreed to in writing, software
	* distributed under the License is distributed on an "AS IS" BASIS,
	* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	* See the License for the specific language governing permissions and
	* limitations under the License.
	*/
	package opennlp.tools.textsimilarity.chunker2matcher;

	import java.util.List;

	import junit.framework.TestCase;

	import opennlp.tools.textsimilarity.ParseTreeChunk;
	import opennlp.tools.textsimilarity.ParseTreeChunkListScorer;
	import opennlp.tools.textsimilarity.TextSimilarityBagOfWords;

	public class ParserChunker2MatcherProcessorTest extends TestCase {
	private ParserChunker2MatcherProcessor parser;
	private TextSimilarityBagOfWords parserBOW = new TextSimilarityBagOfWords();
	private ParseTreeChunkListScorer parseTreeChunkListScorer = new ParseTreeChunkListScorer();

	public void testGroupedPhrasesFormer() {
	parser = ParserChunker2MatcherProcessor.getInstance();
	String text = "Where do I apply? Go to your town office or city hall. If your town doesn't have an office, ask the town clerk or a Selectman. Tell them that you need a 1040 tax form . I Can 't Pay the Taxes on my House: What Can I Do?. Pine Tree Legal";

	List<List<ParseTreeChunk>> res = parser
	.formGroupedPhrasesFromChunksForPara(text);
	System.out.println(res);
	assertEquals(
	"[[NP [PRP$-your NN-town NN-office CC-or NN-city NN-hall ], NP [PRP$-your NN-town NN-doesn NN-t ], NP [DT-an NN-office ], NP [DT-the NN-town NN-clerk CC-or DT-a NNP-Selectman ], NP [DT-a NNP-Selectman ], NP [PRP-them IN-that PRP-you ], NP [PRP-you ], NP [DT-a CD-1040 NN-tax NN-form ], NP [PRP-I ], NP [DT-the NNS-Taxes IN-on PRP$-my NNP-House WP-What MD-Can PRP-I ], NP [PRP$-my NNP-House WP-What MD-Can PRP-I ], NP [WP-What MD-Can PRP-I ], NP [PRP-I ], NP [NNP-Pine NNP-Tree NNP-Legal ]], [VP [VBP-do RB-I VB-apply ], VP [VB-Go TO-to PRP$-your NN-town NN-office CC-or NN-city NN-hall ], VP [VBP-have DT-an NN-office ], VP [VB-ask DT-the NN-town NN-clerk CC-or DT-a NNP-Selectman ], VP [VB-Tell PRP-them IN-that PRP-you ], VP [VBP-need DT-a CD-1040 NN-tax NN-form ], VP [MD-Can VB-t VB-Pay DT-the NNS-Taxes IN-on PRP$-my NNP-House WP-What MD-Can PRP-I ], VP [VB-Do ]], [PP [TO-to PRP$-your NN-town NN-office CC-or NN-city NN-hall ], PP [IN-on PRP$-my NNP-House WP-What MD-Can PRP-I ]], [], [SENTENCE [WRB-Where VBP-do RB-I VB-apply ], SENTENCE [VB-Go TO-to PRP$-your NN-town NN-office CC-or NN-city NN-hall ], SENTENCE [IN-If PRP$-your NN-town NN-doesn NN-t VBP-have DT-an NN-office VB-ask DT-the NN-town NN-clerk CC-or DT-a NNP-Selectman ], SENTENCE [VB-Tell PRP-them IN-that PRP-you VBP-need DT-a CD-1040 NN-tax NN-form ], SENTENCE [PRP-I MD-Can VB-t VB-Pay DT-the NNS-Taxes IN-on PRP$-my NNP-House WP-What MD-Can PRP-I VB-Do ], SENTENCE [NNP-Pine NNP-Tree NNP-Legal ]]]",
	// "[[NP [PRP$-your NN-town NN-office CC-or NN-city NN-hall ], NP [PRP$-your NN-town NN-doesn NN-t ], NP [DT-an NN-office ], NP [DT-the NN-town NN-clerk CC-or DT-a NNP-Selectman ], NP [DT-a NNP-Selectman ], NP [PRP-them IN-that PRP-you ], NP [PRP-you ], NP [DT-a CD-1040 NN-tax NN-form ], NP [PRP-I ], NP [DT-the NNS-Taxes IN-on PRP$-my NNP-House WP-What MD-Can PRP-I ], NP [PRP$-my NNP-House WP-What MD-Can PRP-I ], NP [WP-What MD-Can PRP-I ], NP [PRP-I ], NP [NNP-Pine NNP-Tree NNP-Legal ]], [VP [VBP-do RB-I VB-apply ], VP [VB-Go TO-to PRP$-your NN-town NN-office CC-or NN-city NN-hall ], VP [VBP-have DT-an NN-office ], VP [VB-ask DT-the NN-town NN-clerk CC-or DT-a NNP-Selectman ], VP [VB-Tell PRP-them IN-that PRP-you ], VP [VBP-need DT-a CD-1040 NN-tax NN-form ], VP [MD-Can VB-t VB-Pay DT-the NNS-Taxes IN-on PRP$-my NNP-House WP-What MD-Can PRP-I ], VP [VB-Do NNP-Pine NNP-Tree NNP-Legal ]], [PP [TO-to PRP$-your NN-town NN-office CC-or NN-city NN-hall ], PP [IN-on PRP$-my NNP-House WP-What MD-Can PRP-I ]], [], [SENTENCE [WRB-Where VBP-do RB-I VB-apply ], SENTENCE [VB-Go TO-to PRP$-your NN-town NN-office CC-or NN-city NN-hall ], SENTENCE [IN-If PRP$-your NN-town NN-doesn NN-t VBP-have DT-an NN-office VB-ask DT-the NN-town NN-clerk CC-or DT-a NNP-Selectman ], SENTENCE [VB-Tell PRP-them IN-that PRP-you VBP-need DT-a CD-1040 NN-tax NN-form ], SENTENCE [PRP-I MD-Can VB-t VB-Pay DT-the NNS-Taxes IN-on PRP$-my NNP-House WP-What MD-Can PRP-I VB-Do NNP-Pine NNP-Tree NNP-Legal ]]]",
	res.toString());

	res = parser
	.formGroupedPhrasesFromChunksForSentence("How can I get short focus zoom lens for digital camera");
	assertEquals(
	"[[NP [PRP-I ], NP [JJ-short NN-focus NN-zoom NN-lens IN-for JJ-digital NN-camera ], NP [JJ-digital NN-camera ]], [VP [VB-get JJ-short NN-focus NN-zoom NN-lens IN-for JJ-digital NN-camera ]], [PP [IN-for JJ-digital NN-camera ]], [], [SENTENCE [WRB-How MD-can PRP-I VB-get JJ-short NN-focus NN-zoom NN-lens IN-for JJ-digital NN-camera ]]]",
	res.toString());

	res = parser
	.formGroupedPhrasesFromChunksForSentence("Its classy design and the Mercedes name make it a very cool vehicle to drive. ");
	assertEquals(
	"[[NP [PRP$-Its JJ-classy NN-design CC-and DT-the NNP-Mercedes NN-name ], NP [DT-the NNP-Mercedes NN-name ], NP [PRP-it DT-a RB-very JJ-cool NN-vehicle TO-to NN-drive ], NP [DT-a RB-very JJ-cool NN-vehicle TO-to NN-drive ], NP [NN-drive ]], [VP [VBP-make PRP-it DT-a RB-very JJ-cool NN-vehicle TO-to NN-drive ]], [PP [TO-to NN-drive ]], [], [SENTENCE [PRP$-Its JJ-classy NN-design CC-and DT-the NNP-Mercedes NN-name VBP-make PRP-it DT-a RB-very JJ-cool NN-vehicle TO-to NN-drive ]]]",
	res.toString());
	res = parser
	.formGroupedPhrasesFromChunksForSentence("Sounds too good to be true but it actually is, the world's first flying car is finally here. ");
	assertEquals(
	"[[NP [PRP-it RB-actually ], NP [DT-the NN-world NNS-s JJ-first NN-flying NN-car ]], [VP [VBZ-Sounds RB-too JJ-good ], VP [TO-to VB-be JJ-true CC-but PRP-it RB-actually ], VP [VBZ-is DT-the NN-world NNS-s JJ-first NN-flying NN-car ], VP [VBZ-is RB-finally RB-here ]], [], [ADJP [RB-too JJ-good ], ADJP [JJ-true CC-but PRP-it RB-actually ]], [SENTENCE [VBZ-Sounds RB-too JJ-good TO-to VB-be JJ-true CC-but PRP-it RB-actually VBZ-is DT-the NN-world NNS-s JJ-first NN-flying NN-car VBZ-is RB-finally RB-here ]]]",
	res.toString());
	res = parser
	.formGroupedPhrasesFromChunksForSentence("UN Ambassador Ron Prosor repeated the Israeli position that the only way the Palestinians will get UN membership and statehood is through direct negotiations with the Israelis on a comprehensive peace agreement");
	assertEquals(
	"[[NP [NNP-UN NNP-Ambassador NNP-Ron NNP-Prosor ], NP [DT-the JJ-Israeli NN-position IN-that DT-the JJ-only NN-way DT-the NNPS-Palestinians ], NP [DT-the JJ-only NN-way DT-the NNPS-Palestinians ], NP [DT-the NNPS-Palestinians ], NP [NN-membership CC-and NN-statehood VBZ-is IN-through JJ-direct NNS-negotiations IN-with DT-the NNP-Israelis IN-on DT-a JJ-comprehensive NN-peace NN-agreement ], NP [JJ-direct NNS-negotiations IN-with DT-the NNP-Israelis IN-on DT-a JJ-comprehensive NN-peace NN-agreement ], NP [DT-the NNP-Israelis IN-on DT-a JJ-comprehensive NN-peace NN-agreement ], NP [DT-a JJ-comprehensive NN-peace NN-agreement ]], [VP [VBD-repeated DT-the JJ-Israeli NN-position IN-that DT-the JJ-only NN-way DT-the NNPS-Palestinians ], VP [MD-will VB-get IN-UN NN-membership CC-and NN-statehood VBZ-is IN-through JJ-direct NNS-negotiations IN-with DT-the NNP-Israelis IN-on DT-a JJ-comprehensive NN-peace NN-agreement ]], [PP [IN-that DT-the JJ-only NN-way DT-the NNPS-Palestinians ], PP [IN-UN NN-membership CC-and NN-statehood VBZ-is IN-through JJ-direct NNS-negotiations IN-with DT-the NNP-Israelis IN-on DT-a JJ-comprehensive NN-peace NN-agreement ], PP [IN-through JJ-direct NNS-negotiations IN-with DT-the NNP-Israelis IN-on DT-a JJ-comprehensive NN-peace NN-agreement ], PP [IN-with DT-the NNP-Israelis IN-on DT-a JJ-comprehensive NN-peace NN-agreement ], PP [IN-on DT-a JJ-comprehensive NN-peace NN-agreement ]], [], [SENTENCE [NNP-UN NNP-Ambassador NNP-Ron NNP-Prosor VBD-repeated DT-the JJ-Israeli NN-position IN-that DT-the JJ-only NN-way DT-the NNPS-Palestinians MD-will VB-get IN-UN NN-membership CC-and NN-statehood VBZ-is IN-through JJ-direct NNS-negotiations IN-with DT-the NNP-Israelis IN-on DT-a JJ-comprehensive NN-peace NN-agreement ]]]",
	res.toString());
	parser.close();
	}

	public void testPrintParseTree() {
	parser = ParserChunker2MatcherProcessor.getInstance();
	try {
	parser
	.printParseTree("How can I get short focus zoom lens for digital camera");
	} catch (Exception e) {
	// when models does not read
	}
	parser.close();
	}

	public void testRelevanceAssessm() {
	parser = ParserChunker2MatcherProcessor.getInstance();
	String phrase1 = "Its classy design and the Mercedes name make it a very cool vehicle to drive. "
	+ "The engine makes it a powerful car. "
	+ "The strong engine gives it enough power. "
	+ "The strong engine gives the car a lot of power.";
	String phrase2 = "This car has a great engine. "
	+ "This car has an amazingly good engine. "
	+ "This car provides you a very good mileage.";

	System.out.println(parser.assessRelevance(phrase1, phrase2)
	.getMatchResult());
	parser.close();

	}

	public void testCompareRelevanceAssessmWithBagOfWords() {
	parser = ParserChunker2MatcherProcessor.getInstance();
	// we first demonstrate how similarity expression for DIFFERENT cases have
	// too high score for bagOfWords
	String phrase1 = "How to deduct rental expense from income ";
	String phrase2 = "How to deduct repair expense from rental income.";
	List<List<ParseTreeChunk>> matchResult = parser.assessRelevance(phrase1,
	phrase2).getMatchResult();
	assertEquals(
	"[[ [NN-expense IN-from NN-income ], [JJ-rental NN-* ]], [ [TO-to VB-deduct JJ-rental NN-* ], [VB-deduct NN-expense IN-from NN-income ]]]",
	matchResult.toString());
	System.out.println(matchResult);
	double matchScore = parseTreeChunkListScorer
	.getParseTreeChunkListScore(matchResult);
	double bagOfWordsScore = parserBOW.assessRelevanceAndGetScore(phrase1,
	phrase2);
	assertTrue(matchScore + 2 < bagOfWordsScore);
	System.out.println("MatchScore is adequate ( = " + matchScore
	+ ") and bagOfWordsScore = " + bagOfWordsScore + " is too high");

	// we now demonstrate how similarity can be captured by POS and cannot be
	// captured by bagOfWords
	phrase1 = "Way to minimize medical expense for my daughter";
	phrase2 = "Means to deduct educational expense for my son";
	matchResult = parser.assessRelevance(phrase1, phrase2).getMatchResult();
	assertEquals(
	"[[ [JJ-* NN-expense IN-for PRP$-my NN-* ]], [ [TO-to VB-* JJ-* NN-expense IN-for PRP$-my NN-* ]]]",
	matchResult.toString());
	System.out.println(matchResult);
	matchScore = parseTreeChunkListScorer
	.getParseTreeChunkListScore(matchResult);
	bagOfWordsScore = parserBOW.assessRelevanceAndGetScore(phrase1, phrase2);
	assertTrue(matchScore > 2 * bagOfWordsScore);
	System.out.println("MatchScore is adequate ( = " + matchScore
	+ ") and bagOfWordsScore = " + bagOfWordsScore + " is too low");
	parser.close();

	}
	}