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Stanford Parser processes raw text in English, Chinese, German, Arabic, and French, and extracts constituency parse trees.

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package edu.stanford.nlp.parser.lexparser;

import edu.stanford.nlp.trees.TreePrint;
import edu.stanford.nlp.trees.TreebankLanguagePack;

import java.io.Serializable;
import java.util.Properties;

/**
 * Options to the parser which affect performance only at testing (parsing)
 * time.
 * 
* The Options class that stores the TestOptions stores the * TestOptions as a transient object. This means that whatever * options get set at creation time are forgotten when the parser is * serialized. If you want an option to be remembered when the parser * is reloaded, put it in either TrainOptions or in Options itself. * * @author Dan Klein */ public class TestOptions implements Serializable { static final String DEFAULT_PRE_TAGGER = "/u/nlp/data/pos-tagger/distrib/wsj-0-18-bidirectional-nodistsim.tagger"; public TestOptions() { evals = new Properties(); evals.setProperty("pcfgLB", "true"); evals.setProperty("depDA", "true"); evals.setProperty("factLB", "true"); evals.setProperty("factTA", "true"); evals.setProperty("summary", "true"); } /** * If false, then failure of the PCFG parser to parse a sentence * will trigger allowing all tags for words in parse recovery mode, * with a log probability of -1000. * If true, these extra taggings are not added. * It is false by default. Use option -noRecoveryTagging to set * to true. */ public boolean noRecoveryTagging = false; /** If true, then failure of the PCFG factor to parse a sentence * will trigger parse recovery mode. */ public boolean doRecovery = true; /** * If true, the n^4 "speed-up" is not used with the Factored Parser. */ public boolean useN5 = false; /** If true, use approximate factored algorithm, which just rescores * PCFG k best, rather than exact factored algorithm. This algorithm * requires the dependency grammar to exist for rescoring, but not for * the dependency grammar to be run. Hence the correct usage for * guarding code only required for exact A* factored parsing is now * if (op.doPCFG && op.doDep && ! Test.useFastFactored). */ public boolean useFastFactored = false; /** If true, use faster iterative deepening CKY algorithm. */ public boolean iterativeCKY = false; /** * The maximum sentence length (including punctuation, etc.) to parse. */ public int maxLength = -0xDEADBEEF; // initial value is -0xDEADBEEF (actually positive because of 2s complement) /** * The maximum number of edges and hooks combined that the factored parser * will build before giving up. This number should probably be relative to * the sentence length parsed. In general, though, if the parser cannot parse * a sentence after this much work then there is no good parse consistent * between the PCFG and Dependency parsers. (Normally, depending on other * flags), the parser will then just return the best PCFG parse.) */ public int MAX_ITEMS = 200000; /** * The amount of smoothing put in (as an m-estimate) for unknown words. * If negative, set by the code in the lexicon class. */ public double unseenSmooth = -1.0; /** * Parse trees in test treebank in order of increasing length. */ public boolean increasingLength = false; /** * Tag the sentences first, then parse given those (coarse) tags. */ public boolean preTag = false; /** * Parse using only tags given from correct answer or the POS tagger */ public boolean forceTags = preTag; public boolean forceTagBeginnings = false; /** * POS tagger model used when preTag is enabled. */ public String taggerSerializedFile = DEFAULT_PRE_TAGGER; /** * Only valid with force tags - strips away functionals when forcing * the tags, meaning tags have to start * appropriately but the parser will assign the functional part. */ public boolean noFunctionalForcing = preTag; /** * Write EvalB-readable output files. */ public boolean evalb = false; /** * Print a lot of extra output as you parse. */ public boolean verbose = false; // Don't change this; set with -v public final boolean exhaustiveTest = false; /** If this variable is true, and the sum of the inside and outside score * for a constituent is worse than the best known score for a sentence by * more than pcfgThresholdValue, then -Inf is returned as the * outside Score by oScore() (while otherwise the true * outside score is returned). */ public final boolean pcfgThreshold = false; public final double pcfgThresholdValue = -2.0; /** * Print out all best PCFG parses. */ public boolean printAllBestParses = false; /** * Weighting on dependency log probs. The dependency grammar negative log * probability scores are simply multiplied by this number. */ public double depWeight = 1.0; public boolean prunePunc = false; /** If a token list does not have sentence final punctuation near the * end, then automatically add the default one. * This might help parsing if the treebank is all punctuated. * Not done if reading a treebank. */ public boolean addMissingFinalPunctuation; /** * Determines format of output trees: choose among penn, oneline */ public String outputFormat = "penn"; public String outputFormatOptions = ""; /** If true, write files parsed to a new file with the same name except * for an added ".stp" extension. */ public boolean writeOutputFiles; /** If the writeOutputFiles option is true, then output files appear in * this directory. An unset value (null) means to use * the directory of the source files. Use "" or . * for the current directory. */ public String outputFilesDirectory; /** If the writeOutputFiles option is true, then output files appear with * this extension. Use "" for no extension. */ public String outputFilesExtension = "stp"; /** * If the writeOutputFiles option is true, then output files appear with * this prefix. */ public String outputFilesPrefix = "parses"; /** * If this option is not null, output the k-best equivocation. Must be specified * with printPCFGkBest. */ public String outputkBestEquivocation; /** * The largest span to consider for word-hood. Used for parsing unsegmented * Chinese text and parsing lattices. Keep it at 1 unless you know what * you're doing. */ public int maxSpanForTags = 1; /** * Turns on normalizing scores for sentence length. Makes no difference * (except decreased efficiency) unless maxSpanForTags is greater than one. * Works only for PCFG (so far). */ public boolean lengthNormalization = false; /** * Used when you want to generate sample parses instead of finding the best * parse. (NOT YET USED.) */ public boolean sample = false; /** Printing k-best parses from PCFG, when k > 0. */ public int printPCFGkBest = 0; /** If using a kBest eval, use this many trees. */ public int evalPCFGkBest = 100; /** Printing k-best parses from PCFG, when k > 0. */ public int printFactoredKGood = 0; /** What evaluations to report and how to report them * (using LexicalizedParser). Known evaluations * are: pcfgLB, pcfgCB, pcfgDA, pcfgTA, pcfgLL, pcfgRUO, pcfgCUO, pcfgCatE, * pcfgChildSpecific, * depDA, depTA, depLL, * factLB, factCB, factDA, factTA, factLL, factChildSpecific. * The default is pcfgLB,depDA,factLB,factTA. You need to negate those * ones out (e.g., -evals "depDA=false") if you don't want * them. * LB = ParseEval labeled bracketing,
* CB = crossing brackets and zero crossing bracket rate,
* DA = dependency accuracy, TA = tagging accuracy,
* LL = log likelihood score,
* RUO/CUO = rules/categories under and over proposed,
* CatE = evaluation by phrasal category.
* ChildSpecific: supply an argument with =. F1 will be returned * for only the nodes which have at least one child that matches * this regular expression.
* Known styles are: runningAverages, summary, tsv.
* The default style is summary. * You need to negate it out if you don't want it. * Invalid names in the argument to this option are not reported! */ public Properties evals; /** This variable says to find k good fast factored parses, how many times * k of the best PCFG parses should be examined. */ public int fastFactoredCandidateMultiplier = 3; /** This variable says to find k good factored parses, how many added on * best PCFG parses should be examined. */ public int fastFactoredCandidateAddend = 50; /** If this is true, the Lexicon is used to score P(w|t) in the backoff inside the * dependency grammar. (Otherwise, a MLE is used is w is seen, and a constant if * w is unseen. */ public boolean useLexiconToScoreDependencyPwGt = false; /** If this is true, perform non-projective dependency parsing. */ public boolean useNonProjectiveDependencyParser = false; /** * Number of threads to use at test time. For example, * -testTreebank can use this to go X times faster, with the * negative consequence that output is not quite as nicely ordered. */ public int testingThreads = 1; /** * When evaluating, don't print out tons of text. Only print out the final scores */ public boolean quietEvaluation = false; /** * Determines method for print trees on output. * * @param tlpParams The treebank parser params * @return A suitable tree printing object */ public TreePrint treePrint(TreebankLangParserParams tlpParams) { TreebankLanguagePack tlp = tlpParams.treebankLanguagePack(); return new TreePrint(outputFormat, outputFormatOptions, tlp, tlpParams.headFinder(), tlpParams.typedDependencyHeadFinder()); } public void display() { String str = toString(); System.err.println(str); } @Override public String toString() { return ("Test parameters" + " maxLength=" + maxLength + " preTag=" + preTag + " outputFormat=" + outputFormat + " outputFormatOptions=" + outputFormatOptions + " printAllBestParses=" + printAllBestParses + " testingThreads=" + testingThreads + " quietEvaluation=" + quietEvaluation); } private static final long serialVersionUID = 7256526346598L; }




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