Examples with Tree edu.stanford.nlp.trees.Tree used on opensource projects

Example 6 with Tree

use of edu.stanford.nlp.trees.Tree in project CoreNLP by stanfordnlp.

the class NegraPennCollinizer method transformTree.

public Tree transformTree(Tree tree) {
    Label l = tree.label();
    if (tree.isLeaf()) {
        return tf.newLeaf(l);
    }
    String s = l.value();
    s = tlpp.treebankLanguagePack().basicCategory(s);
    if (deletePunct) {
        // since it ignores punctuation anyway
        if (tree.isPreTerminal() && tlpp.treebankLanguagePack().isEvalBIgnoredPunctuationTag(s)) {
            return null;
        }
    }
    // TEMPORARY: eliminate the TOPP constituent
    if (tree.children()[0].label().value().equals("TOPP")) {
        log.info("Found a TOPP");
        tree.setChildren(tree.children()[0].children());
    }
    // Negra has lots of non-unary roots; delete unary roots
    if (tlpp.treebankLanguagePack().isStartSymbol(s) && tree.numChildren() == 1) {
        // NB: This deletes the boundary symbol, which is in the tree!
        return transformTree(tree.getChild(0));
    }
    List<Tree> children = new ArrayList<>();
    for (int cNum = 0, numC = tree.numChildren(); cNum < numC; cNum++) {
        Tree child = tree.getChild(cNum);
        Tree newChild = transformTree(child);
        if (newChild != null) {
            children.add(newChild);
        }
    }
    if (children.isEmpty()) {
        return null;
    }
    return tf.newTreeNode(new StringLabel(s), children);
}

Example 7 with Tree

use of edu.stanford.nlp.trees.Tree in project CoreNLP by stanfordnlp.

the class NodePruner method helper.

private List<Tree> helper(List<Tree> treeList, int start) {
    List<Tree> newTreeList = new ArrayList<>(treeList.size());
    for (Tree tree : treeList) {
        int end = start + tree.yield().size();
        newTreeList.add(prune(tree, start));
        start = end;
    }
    return newTreeList;
}

Example 8 with Tree

use of edu.stanford.nlp.trees.Tree in project CoreNLP by stanfordnlp.

the class HTKLatticeReader method main.

public static void main(String[] args) throws Exception {
    boolean mergeType = USESUM;
    boolean prettyPrint = true;
    boolean debug = false;
    String parseGram = null;
    String filename = args[0];
    for (int i = 1; i < args.length; i++) {
        if (args[i].equalsIgnoreCase("-debug")) {
            debug = true;
        } else if (args[i].equalsIgnoreCase("-useMax")) {
            mergeType = USEMAX;
        } else if (args[i].equalsIgnoreCase("-useSum")) {
            mergeType = USESUM;
        } else if (args[i].equalsIgnoreCase("-noPrettyPrint")) {
            prettyPrint = false;
        } else if (args[i].equalsIgnoreCase("-parser")) {
            parseGram = args[++i];
        } else {
            log.info("unrecognized flag: " + args[i]);
            log.info("usage: java LatticeReader <file> [ -debug ] [ -useMax ] [ -useSum ] [ -noPrettyPrint ] [ -parser parserFile ]");
            System.exit(0);
        }
    }
    HTKLatticeReader lr = new HTKLatticeReader(filename, mergeType, debug, prettyPrint);
    if (parseGram != null) {
        Options op = new Options();
        // TODO: these options all get clobbered by the Options object
        // stored in the LexicalizedParser (unless it's a text file?)
        op.doDep = false;
        op.testOptions.maxLength = 80;
        op.testOptions.maxSpanForTags = 80;
        LexicalizedParser lp = LexicalizedParser.loadModel(parseGram, op);
        // TODO: somehow merge this into ParserQuery instead of being
        // LexicalizedParserQuery specific
        LexicalizedParserQuery pq = lp.lexicalizedParserQuery();
        pq.parse(lr);
        Tree t = pq.getBestParse();
        t.pennPrint();
    }
//lr.processLattice();
}

Example 9 with Tree

use of edu.stanford.nlp.trees.Tree in project CoreNLP by stanfordnlp.

the class CollinsDepEval method main.

/**
   * 
   * @param args
   */
public static void main(String[] args) {
    if (args.length < MIN_ARGS) {
        log.info(usage());
        System.exit(-1);
    }
    Properties options = StringUtils.argsToProperties(args, optionArgDefs());
    boolean VERBOSE = PropertiesUtils.getBool(options, "v", false);
    Language LANGUAGE = PropertiesUtils.get(options, "l", Language.English, Language.class);
    int MAX_GOLD_YIELD = PropertiesUtils.getInt(options, "g", Integer.MAX_VALUE);
    int MAX_GUESS_YIELD = PropertiesUtils.getInt(options, "y", Integer.MAX_VALUE);
    String[] parsedArgs = options.getProperty("", "").split("\\s+");
    if (parsedArgs.length != MIN_ARGS) {
        log.info(usage());
        System.exit(-1);
    }
    File goldFile = new File(parsedArgs[0]);
    File guessFile = new File(parsedArgs[1]);
    final TreebankLangParserParams tlpp = LANGUAGE.params;
    final PrintWriter pwOut = tlpp.pw();
    final Treebank guessTreebank = tlpp.diskTreebank();
    guessTreebank.loadPath(guessFile);
    pwOut.println("GUESS TREEBANK:");
    pwOut.println(guessTreebank.textualSummary());
    final Treebank goldTreebank = tlpp.diskTreebank();
    goldTreebank.loadPath(goldFile);
    pwOut.println("GOLD TREEBANK:");
    pwOut.println(goldTreebank.textualSummary());
    final CollinsDepEval depEval = new CollinsDepEval("CollinsDep", true, tlpp.headFinder(), tlpp.treebankLanguagePack().startSymbol());
    final TreeTransformer tc = tlpp.collinizer();
    //PennTreeReader skips over null/malformed parses. So when the yields of the gold/guess trees
    //don't match, we need to keep looking for the next gold tree that matches.
    //The evalb ref implementation differs slightly as it expects one tree per line. It assigns
    //status as follows:
    //
    //   0 - Ok (yields match)
    //   1 - length mismatch
    //   2 - null parse e.g. (()).
    //
    //In the cases of 1,2, evalb does not include the tree pair in the LP/LR computation.
    final Iterator<Tree> goldItr = goldTreebank.iterator();
    int goldLineId = 0;
    int skippedGuessTrees = 0;
    for (final Tree guess : guessTreebank) {
        final Tree evalGuess = tc.transformTree(guess);
        if (guess.yield().size() > MAX_GUESS_YIELD) {
            skippedGuessTrees++;
            continue;
        }
        boolean doneEval = false;
        while (goldItr.hasNext() && !doneEval) {
            final Tree gold = goldItr.next();
            final Tree evalGold = tc.transformTree(gold);
            goldLineId++;
            if (gold.yield().size() > MAX_GOLD_YIELD) {
                continue;
            } else if (evalGold.yield().size() != evalGuess.yield().size()) {
                pwOut.println("Yield mismatch at gold line " + goldLineId);
                skippedGuessTrees++;
                //Default evalb behavior -- skip this guess tree
                break;
            }
            depEval.evaluate(evalGuess, evalGold, ((VERBOSE) ? pwOut : null));
            //Move to the next guess parse
            doneEval = true;
        }
    }
    pwOut.println("================================================================================");
    if (skippedGuessTrees != 0)
        pwOut.printf("%s %d guess trees\n", ((MAX_GUESS_YIELD < Integer.MAX_VALUE) ? "Skipped" : "Unable to evaluate"), skippedGuessTrees);
    depEval.display(true, pwOut);
    pwOut.close();
}

Example 10 with Tree

use of edu.stanford.nlp.trees.Tree in project CoreNLP by stanfordnlp.

the class LeafAncestorEval method main.

/**
   * Execute with no arguments for usage.
   */
public static void main(String[] args) {
    if (!validateCommandLine(args)) {
        log.info(USAGE);
        System.exit(-1);
    }
    final TreebankLangParserParams tlpp = LANGUAGE.params;
    final PrintWriter pwOut = tlpp.pw();
    final Treebank guessTreebank = tlpp.diskTreebank();
    guessTreebank.loadPath(guessFile);
    pwOut.println("GUESS TREEBANK:");
    pwOut.println(guessTreebank.textualSummary());
    final Treebank goldTreebank = tlpp.diskTreebank();
    goldTreebank.loadPath(goldFile);
    pwOut.println("GOLD TREEBANK:");
    pwOut.println(goldTreebank.textualSummary());
    final LeafAncestorEval metric = new LeafAncestorEval("LeafAncestor");
    final TreeTransformer tc = tlpp.collinizer();
    //The evalb ref implementation assigns status for each tree pair as follows:
    //
    //   0 - Ok (yields match)
    //   1 - length mismatch
    //   2 - null parse e.g. (()).
    //
    //In the cases of 1,2, evalb does not include the tree pair in the LP/LR computation.
    final Iterator<Tree> goldItr = goldTreebank.iterator();
    final Iterator<Tree> guessItr = guessTreebank.iterator();
    int goldLineId = 0;
    int guessLineId = 0;
    int skippedGuessTrees = 0;
    while (guessItr.hasNext() && goldItr.hasNext()) {
        Tree guessTree = guessItr.next();
        List<Label> guessYield = guessTree.yield();
        guessLineId++;
        Tree goldTree = goldItr.next();
        List<Label> goldYield = goldTree.yield();
        goldLineId++;
        // Check that we should evaluate this tree
        if (goldYield.size() > MAX_GOLD_YIELD) {
            skippedGuessTrees++;
            continue;
        }
        // Only trees with equal yields can be evaluated
        if (goldYield.size() != guessYield.size()) {
            pwOut.printf("Yield mismatch gold: %d tokens vs. guess: %d tokens (lines: gold %d guess %d)%n", goldYield.size(), guessYield.size(), goldLineId, guessLineId);
            skippedGuessTrees++;
            continue;
        }
        final Tree evalGuess = tc.transformTree(guessTree);
        final Tree evalGold = tc.transformTree(goldTree);
        metric.evaluate(evalGuess, evalGold, ((VERBOSE) ? pwOut : null));
    }
    if (guessItr.hasNext() || goldItr.hasNext()) {
        System.err.printf("Guess/gold files do not have equal lengths (guess: %d gold: %d)%n.", guessLineId, goldLineId);
    }
    pwOut.println("================================================================================");
    if (skippedGuessTrees != 0)
        pwOut.printf("%s %d guess trees%n", "Unable to evaluate", skippedGuessTrees);
    metric.display(true, pwOut);
    pwOut.close();
}