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Stanford CoreNLP provides a set of natural language analysis tools which can take raw English language text input and give the base forms of words, their parts of speech, whether they are names of companies, people, etc., normalize dates, times, and numeric quantities, mark up the structure of sentences in terms of phrases and word dependencies, and indicate which noun phrases refer to the same entities. It provides the foundational building blocks for higher level text understanding applications.

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package edu.stanford.nlp.parser.lexparser;

import java.io.PrintWriter;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;

import edu.stanford.nlp.ling.HasWord;
import edu.stanford.nlp.parser.KBestViterbiParser;
import edu.stanford.nlp.parser.common.NoSuchParseException;
import edu.stanford.nlp.parser.common.ParserConstraint;
import edu.stanford.nlp.parser.common.ParserQuery;
import edu.stanford.nlp.trees.Tree;
import edu.stanford.nlp.util.Generics;
import edu.stanford.nlp.util.ScoredComparator;
import edu.stanford.nlp.util.ScoredObject;

/**
 * Rerank trees from the ParserQuery based on scores from a Reranker.
 * 
* TODO: should handle Factored parsers as well * * @author John Bauer */ public class RerankingParserQuery implements ParserQuery { private final Options op; private final ParserQuery parserQuery; private final Reranker reranker; private final int rerankerKBest; private List> scoredTrees; /** * Data for this particular query stored by the Reranker will be * stored in this object */ private RerankerQuery rerankerQuery; public RerankingParserQuery(Options op, ParserQuery parserQuery, Reranker reranker) { this.op = op; this.parserQuery = parserQuery; this.reranker = reranker; this.rerankerKBest = op.rerankerKBest; } @Override public boolean saidMemMessage() { return parserQuery.saidMemMessage(); } @Override public void setConstraints(List constraints) { parserQuery.setConstraints(constraints); } @Override public boolean parse(List sentence) { boolean success = parserQuery.parse(sentence); if (!success) { return false; } List> bestKParses = parserQuery.getKBestPCFGParses(rerankerKBest); if (bestKParses.isEmpty()) { return false; } scoredTrees = rerank(sentence, bestKParses); return true; } @Override public boolean parseAndReport(List sentence, PrintWriter pwErr) { boolean success = parserQuery.parseAndReport(sentence, pwErr); if (!success) { return false; } List> bestKParses = parserQuery.getKBestPCFGParses(rerankerKBest); if (bestKParses.isEmpty()) { return false; } scoredTrees = rerank(sentence, bestKParses); return true; } List> rerank(List sentence, List> bestKParses) { this.rerankerQuery = reranker.process(sentence); List> reranked = new ArrayList<>(); for (ScoredObject scoredTree : bestKParses) { double score = scoredTree.score(); try { score = op.baseParserWeight * score + rerankerQuery.score(scoredTree.object()); } catch (NoSuchParseException e) { score = Double.NEGATIVE_INFINITY; } reranked.add(new ScoredObject<>(scoredTree.object(), score)); } Collections.sort(reranked, ScoredComparator.DESCENDING_COMPARATOR); return reranked; } @Override public Tree getBestParse() { if (scoredTrees == null || scoredTrees.isEmpty()) { return null; } return scoredTrees.get(0).object(); } @Override public List> getKBestParses(int k) { return this.getKBestPCFGParses(k); } @Override public double getBestScore() { return this.getPCFGScore(); } @Override public Tree getBestPCFGParse() { return getBestParse(); } @Override public double getPCFGScore() { if (scoredTrees == null || scoredTrees.isEmpty()) { throw new AssertionError(); } return scoredTrees.get(0).score(); } @Override public Tree getBestDependencyParse(boolean debinarize) { // TODO: barf? return null; } @Override public Tree getBestFactoredParse() { // TODO: barf? return null; } @Override public List> getBestPCFGParses() { if (scoredTrees == null || scoredTrees.isEmpty()) { throw new AssertionError(); } List> equalTrees = Generics.newArrayList(); double score = scoredTrees.get(0).score(); int treePos = 0; while (treePos < scoredTrees.size() && scoredTrees.get(treePos).score() == score) { equalTrees.add(scoredTrees.get(treePos)); } return equalTrees; } @Override public void restoreOriginalWords(Tree tree) { parserQuery.restoreOriginalWords(tree); } @Override public boolean hasFactoredParse() { return false; } @Override public List> getKBestPCFGParses(int kbestPCFG) { List> trees = Generics.newArrayList(); for (int treePos = 0; treePos < scoredTrees.size() && treePos < kbestPCFG; ++treePos) { trees.add(scoredTrees.get(treePos)); } return trees; } @Override public List> getKGoodFactoredParses(int kbest) { // TODO: barf? return null; } @Override public KBestViterbiParser getPCFGParser() { return null; } @Override public KBestViterbiParser getFactoredParser() { return null; } @Override public KBestViterbiParser getDependencyParser() { return null; } /** * Parsing succeeded without any horrible errors or fallback */ @Override public boolean parseSucceeded() { return parserQuery.parseSucceeded(); } /** * The sentence was skipped, probably because it was too long or of length 0 */ @Override public boolean parseSkipped() { return parserQuery.parseSkipped(); } /** * The model had to fall back to a simpler model on the previous parse */ @Override public boolean parseFallback() { return parserQuery.parseFallback(); } /** * The model ran out of memory on the most recent parse */ @Override public boolean parseNoMemory() { return parserQuery.parseNoMemory(); } /** * The model could not parse the most recent sentence for some reason */ @Override public boolean parseUnparsable() { return parserQuery.parseUnparsable(); } @Override public List originalSentence() { return parserQuery.originalSentence(); } public RerankerQuery rerankerQuery() { return rerankerQuery; } }




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