Python read_full_results Examples

Example #1

File: crowdflower_results_into_training_data.py Project: WeilerWebServices/Extractors

def main(crowdflower_csv, pos_data_dir, output_file, debug):
    """ Transform the crowdflower results into training data

    :param file crowdflower_csv: The CSV containing crowdflower data
    :param str pos_data_dir: The directory containing POS tagging for each sentence
    :param file output_file: The file in which to write the training data
    :return: 0
    :rtype: int
    """
    results = read_full_results(crowdflower_csv)
    if debug:
        print 'Results from crowdflower'
        print json.dumps(results, indent=2)

    set_majority_vote_answer(results)
    if debug:
        print 'Computed majority vote'
        print json.dumps(results, indent=2)

    tag_entities(results)
    if debug:
        print 'Entities tagged'
        print json.dumps(results, indent=2)

    output = produce_training_data(results, pos_data_dir, debug)
    for l in output:
        output_file.write(l.encode('utf-8') + '\n')

    return 0

Example #2

File: crowdflower_results_into_training_data.py Project: anukat2015/fact-extractor

def main(crowdflower_csv, pos_data_dir, output_file, debug):
    """ Transform the crowdflower results into training data

    :param file crowdflower_csv: The CSV containing crowdflower data
    :param str pos_data_dir: The directory containing POS tagging for each sentence
    :param file output_file: The file in which to write the training data
    :return: 0
    :rtype: int
    """
    results = read_full_results(crowdflower_csv)
    if debug:
        print 'Results from crowdflower'
        print json.dumps(results, indent=2)

    set_majority_vote_answer(results)
    if debug:
        print 'Computed majority vote'
        print json.dumps(results, indent=2)

    tag_entities(results)
    if debug:
        print 'Entities tagged'
        print json.dumps(results, indent=2)

    output = produce_training_data(results, pos_data_dir, debug)
    for l in output:
        output_file.write(l.encode('utf-8') + '\n')

    return 0

Example #3

File: compute_fleiss_kappa.py Project: kyoungrok0517/fact-extractor

def main(crowdflower_output, num_judgments):
    """
    this script computes the agreement of judgments given in the crowdflower
    job using a metric called Fleiss kappa
    """
    cf_results = read_full_results(crowdflower_output)
    mat = compute_matrix(cf_results, num_judgments)
    print computeFleissKappa(mat)

Example #4

def main(crowdflower_output, num_judgments):
    """
    this script computes the agreement of judgments given in the crowdflower
    job using a metric called Fleiss kappa
    """
    cf_results = read_full_results(crowdflower_output)
    mat = compute_matrix(cf_results, num_judgments)
    print computeFleissKappa(mat)

Example #5

File: compute_fleiss_kappa.py Project: WeilerWebServices/Extractors

def main(crowdflower_output, num_judgments):
    """
    this script computes the agreement of judgments given in the crowdflower
    job using a metric called Fleiss kappa
    :param file crowdflower_output: CSV file containing the results from crowdflower
    :param int num_judgments: Consider only this number of results, skip if not enough
    """
    cf_results = read_full_results(crowdflower_output)
    mat = compute_matrix(cf_results, num_judgments)
    print computeFleissKappa(mat)

Example #6

File: compute_fleiss_kappa.py Project: anukat2015/fact-extractor

def main(crowdflower_output, num_judgments):
    """
    this script computes the agreement of judgments given in the crowdflower
    job using a metric called Fleiss kappa
    :param file crowdflower_output: CSV file containing the results from crowdflower
    :param int num_judgments: Consider only this number of results, skip if not enough
    """
    cf_results = read_full_results(crowdflower_output)
    mat = compute_matrix(cf_results, num_judgments)
    print computeFleissKappa(mat)

Example #7

File: crowdflower_results_into_training_data.py Project: kyoungrok0517/fact-extractor

def main(crowdflower_csv, pos_data_dir, output_file, debug):
    results = read_full_results(crowdflower_csv)
    if debug:
        print 'Results from crowdflower'
        print json.dumps(results, indent=2)

    set_majority_vote_answer(results)
    if debug:
        print 'Computed majority vote'
        print json.dumps(results, indent=2)

    tag_entities(results)
    if debug:
        print 'Entities tagged'
        print json.dumps(results, indent=2)

    output = produce_training_data(results, pos_data_dir, debug)
    for l in output:
        output_file.write(l.encode('utf-8') + '\n')

    return 0

Example #8

File: crowdflower_results_into_training_data.py Project: redreamality/fact-extractor

def main(crowdflower_csv, pos_data_dir, output_file, debug):
    results = read_full_results(crowdflower_csv)
    if debug:
        print 'Results from crowdflower'
        print json.dumps(results, indent=2)

    set_majority_vote_answer(results)
    if debug:
        print 'Computed majority vote'
        print json.dumps(results, indent=2)

    tag_entities(results)
    if debug:
        print 'Entities tagged'
        print json.dumps(results, indent=2)

    output = produce_training_data(results, pos_data_dir, debug)
    for l in output:
        output_file.write(l.encode('utf-8') + '\n')

    return 0

Example #9

File: compute_fleiss_kappa.py Project: Sergiuu17/fact-extractor

def main(crowdflower_output, num_judgments):
    cf_results = read_full_results(crowdflower_output)
    mat = compute_matrix(cf_results, num_judgments)
    print computeFleissKappa(mat)