Examples of edu.stanford.nlp.parser.lexparser.EnglishTreebankParserParams.collinizer()

Package edu.stanford.nlp.parser.lexparser

Class edu.stanford.nlp.parser.lexparser.EnglishTreebankParserParams

Examples of edu.stanford.nlp.parser.lexparser.EnglishTreebankParserParams.collinizer()

edu.stanford.nlp.parser.lexparser.EnglishTreebankParserParams.collinizer()
The tree transformer used to produce trees for evaluation. It will be applied both to the parser output and the gold tree.

    pwOut.println(goldTreebank.textualSummary());


    final String evalName = (tagMode) ? "TsarfatyTAG" : "TsarfatySEG";
    final TsarfatyEval eval = new TsarfatyEval(evalName, tagMode);


    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:

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    pwOut.println("GOLD TREEBANK:");
    pwOut.println(goldTreebank.textualSummary());


    final UnlabeledAttachmentEval metric = new UnlabeledAttachmentEval("UAS LP/LR", true, tlpp.headFinder());


    final TreeTransformer tc = tlpp.collinizer();


    //The evalb ref implementation assigns status for each tree pair as follows:
    //
    //   0 - Ok (yields match)
    //   1 - length mismatch

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    pwOut.println("GOLD TREEBANK:");
    pwOut.println(goldTreebank.textualSummary());


    final TaggingEval metric = new TaggingEval("Tagging LP/LR");


    final TreeTransformer tc = tlpp.collinizer();


    //The evalb ref implementation assigns status for each tree pair as follows:
    //
    //   0 - Ok (yields match)
    //   1 - length mismatch

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