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135 changes: 135 additions & 0 deletions
135
itest/src/edu/stanford/nlp/ie/qe/QuantifiableEntityExtractorITest.java
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| @@ -0,0 +1,135 @@ | ||
| package edu.stanford.nlp.ie.qe; | ||
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| import edu.stanford.nlp.ling.tokensregex.MatchedExpression; | ||
| import edu.stanford.nlp.pipeline.*; | ||
| import junit.framework.TestCase; | ||
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| import java.util.List; | ||
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| /** | ||
| * Test for quantifiable entity extractor | ||
| * @author Angel Chang | ||
| */ | ||
| public class QuantifiableEntityExtractorITest extends TestCase { | ||
| static AnnotationPipeline pipeline = null; | ||
| static QuantifiableEntityExtractor extractor = null; | ||
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| public void test() throws Exception { | ||
| // TODO: Enable tests after rules files are added to models | ||
| } | ||
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| @Override | ||
| public void setUp() throws Exception { | ||
| synchronized(QuantifiableEntityExtractorITest.class) { | ||
| if (pipeline == null) { | ||
| pipeline = new AnnotationPipeline(); | ||
| pipeline.addAnnotator(new TokenizerAnnotator(false, "en")); | ||
| pipeline.addAnnotator(new WordsToSentencesAnnotator(false)); | ||
| pipeline.addAnnotator(new POSTaggerAnnotator(DefaultPaths.DEFAULT_POS_MODEL, false)); | ||
| //pipeline.addAnnotator(new QuantifiableEntityNormalizingAnnotator(false, false)); | ||
| } | ||
| extractor = new QuantifiableEntityExtractor(); | ||
| //extractor.init(new Options()); | ||
| } | ||
| } | ||
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| protected static Annotation createDocument(String text) { | ||
| Annotation annotation = new Annotation(text); | ||
| pipeline.annotate(annotation); | ||
| return annotation; | ||
| } | ||
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| public static class ExpectedQuantity { | ||
| String text; | ||
| String normalizedValue; | ||
| String type; | ||
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| public ExpectedQuantity(String text, String normalizedValue, String type) { | ||
| this.text = text; | ||
| this.normalizedValue = normalizedValue; | ||
| this.type = type; | ||
| } | ||
| } | ||
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| public void runAndCheck(String prefix, String[] sentences, ExpectedQuantity[][] expected) throws Exception { | ||
| for (int si = 0; si < sentences.length; si++) { | ||
| String sentence = sentences[si]; | ||
| Annotation annotation = createDocument(sentence); | ||
| List<MatchedExpression> matchedExpressions = extractor.extract(annotation); | ||
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| // Print out matched text and value | ||
| if (expected == null) { | ||
| for (int i = 0; i < matchedExpressions.size(); i++) { | ||
| String text = matchedExpressions.get(i).getText(); | ||
| Object value = matchedExpressions.get(i).getValue(); | ||
| System.out.println(prefix + ": Got expression " + text + " with value " + value); | ||
| } | ||
| assertTrue(prefix + ": No expected provided", false); | ||
| } else { | ||
| int minMatchable = Math.min(expected[si].length, matchedExpressions.size()); | ||
| for (int i = 0; i < minMatchable; i++) { | ||
| ExpectedQuantity expectedQuantity = expected[si][i]; | ||
| MatchedExpression matched = matchedExpressions.get(i); | ||
| SimpleQuantifiableEntity actualQuantity = (SimpleQuantifiableEntity) matched.getValue().get(); | ||
| assertEquals(prefix + ".matched." + si + "." + i + ".text", expectedQuantity.text, matched.getText()); | ||
| assertEquals(prefix + ".matched." + si + "." + i + ".normalizedValue", expectedQuantity.normalizedValue, actualQuantity.toString()); | ||
| assertEquals(prefix + ".matched." + si + "." + i + ".type", expectedQuantity.type, actualQuantity.getUnit().type); | ||
| } | ||
| assertEquals(prefix + ".length." + si, expected[si].length, matchedExpressions.size()); | ||
| } | ||
| } | ||
| } | ||
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| public void _testMoney() throws Exception { | ||
| String[] sentences = { | ||
| "I have 1 dollar and 2 cents.", | ||
| "It cost 10 thousand million dollars." | ||
| }; | ||
| // TODO: merge the 1 dollar and 2 cents | ||
| ExpectedQuantity[][] expected = { | ||
| {new ExpectedQuantity("1 dollar", "$1.00", "MONEY"), new ExpectedQuantity("2 cents", "$0.02", "MONEY")}, | ||
| {new ExpectedQuantity("10 thousand million dollars", "$10000000000.00", "MONEY")} | ||
| }; | ||
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| runAndCheck("testMoney", sentences, expected); | ||
| } | ||
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| public void _testLength() throws Exception { | ||
| String[] sentences = { | ||
| "We are 2 kilometer away.", | ||
| "We are 2 kilometers away.", | ||
| "We turn after 5 miles.", | ||
| "The box is 100 centimeters tall.", | ||
| "The box is 10cm wide.", | ||
| "The box is over 1000 mm long.", | ||
| "The box is 2ft long." | ||
| }; | ||
| ExpectedQuantity[][] expected = { | ||
| {new ExpectedQuantity("2 kilometer", "2000.0m", "LENGTH")}, | ||
| {new ExpectedQuantity("2 kilometers", "2000.0m", "LENGTH")}, | ||
| {new ExpectedQuantity("5 miles", "5.0mi", "LENGTH")}, | ||
| {new ExpectedQuantity("100 centimeters", "1.0m", "LENGTH")}, | ||
| {new ExpectedQuantity("10cm", "0.1m", "LENGTH")}, | ||
| {new ExpectedQuantity("1000 mm", "1.0m", "LENGTH")}, | ||
| {new ExpectedQuantity("2ft", "2.0'", "LENGTH")} | ||
| }; | ||
| runAndCheck("testLength", sentences, expected); | ||
| } | ||
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| // We do weight instead of mass since in typical natural language | ||
| // kilograms are used to refer to weight vs mass (in scientific usage) | ||
| public void _testWeight() throws Exception { | ||
| String[] sentences = { | ||
| "The ball is 2 kilograms in weight.", | ||
| "There are five grams.", | ||
| "How much is seven pounds?" | ||
| }; | ||
| ExpectedQuantity[][] expected = { | ||
| {new ExpectedQuantity("2 kilograms", "2.0kg", "WEIGHT")}, | ||
| {new ExpectedQuantity("five grams", "0.005kg", "WEIGHT")}, | ||
| {new ExpectedQuantity("seven pounds", "7.0lb", "WEIGHT")} | ||
| }; | ||
| runAndCheck("testWeight", sentences, expected); | ||
| } | ||
|
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| } |
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5 changes: 4 additions & 1 deletion
5
...lp/loglinear/learning/CoNLLBenchmark.java → ...tanford/nlp/loglinear/CoNLLBenchmark.java
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