Examples of edu.ucla.sspace.wordsi.EvaluationWordsi

edu.ucla.sspace.wordsi.EvaluationWordsi

An {@link Wordsi} implementation to be used for evaluations. The word sensesare not updated during processing, instead, each generated context vector is compared to the existing word senses and context vector is labeled with the id for the most similar sense. The sense labeling is passed on directly to the {@link AssignmentReporter} for each context vector generated.

Word sense must be provided by a {@link SemanticSpace}. For any polysemous words, the first sense must be keyed by the raw word and all other sense must be keyed by the raw word plus "-senseNumber" where senseNumber is an integer starting at 1, for the second sense, and goes up to N-1, for the last sense. @author Keith Stevens

            try {
                SemanticSpace sspace = SemanticSpaceIO.load(
                        options.getStringOption('e'));
                if (options.hasOption('E'))
                    reporter = new SemEvalReporter(System.out);
                return new EvaluationWordsi(
                        getAcceptedWords(), getExtractor(), sspace, reporter);
            } catch (IOException ioe) {
                throw new IOError(ioe);
            }
        } else if (options.hasOption('s')) {

Examples of edu.ucla.sspace.wordsi.EvaluationWordsi

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