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""" |
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Evaluate words embeedings by standard benchmarks. |
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4
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Reference: https://github.com/kudkudak/word-embeddings-benchmarks |
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5
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6
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7
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Word Pairs Tasks |
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8
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9
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1. The WordSimilarity-353 Test Collection |
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10
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http://www.cs.technion.ac.il/~gabr/resources/data/wordsim353/ |
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11
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12
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2. Rubenstein, H., and Goodenough, J. 1965. Contextual correlates of synonymy |
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https://www.seas.upenn.edu/~hansens/conceptSim/ |
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14
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15
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3. Stanford Rare Word (RW) Similarity Dataset |
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https://nlp.stanford.edu/~lmthang/morphoNLM/ |
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17
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18
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4. The Word Relatedness Mturk-771 Test Collection |
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19
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http://www2.mta.ac.il/~gideon/datasets/mturk_771.html |
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20
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21
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5. The MEN Test Collection |
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22
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http://clic.cimec.unitn.it/~elia.bruni/MEN.html |
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24
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6. SimLex-999 |
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https://fh295.github.io/simlex.html |
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27
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7. TR9856 |
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https://www.research.ibm.com/haifa/dept/vst/files/IBM_Debater_(R)_TR9856.v2.zip |
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29
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30
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31
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Analogies Tasks |
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32
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33
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1. Google Analogies (subset of WordRep) |
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34
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https://code.google.com/archive/p/word2vec/source |
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35
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36
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2. MSR - Syntactic Analogies |
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37
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http://research.microsoft.com/en-us/projects/rnn/ |
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""" |
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import os |
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import warnings |
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import pandas as pd |
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from pkg_resources import resource_filename |
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with warnings.catch_warnings(): |
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warnings.simplefilter('ignore', category=FutureWarning) |
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51
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52
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WORD_PAIRS_TASKS = {'WS353': 'wordsim353.tsv', |
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'RG65': 'RG_word.tsv', |
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'RW': 'rw.tsv', |
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'Mturk': 'MTURK-771.tsv', |
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'MEN': 'MEN_dataset_natural_form_full.tsv', |
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'SimLex999': 'SimLex-999.tsv', |
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'TR9856': 'TermRelatednessResults.tsv'} |
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60
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ANALOGIES_TASKS = {'MSR-syntax': 'MSR-syntax.txt', |
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'Google': 'questions-words.txt'} |
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62
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63
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PAIR_WORDS_EVALUATION_FIELDS = ['pearson_r', 'pearson_pvalue', |
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'spearman_r', 'spearman_pvalue', |
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65
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'ratio_unkonwn_words'] |
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66
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67
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68
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def get_data_resource_path(filename): |
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return resource_filename(__name__, os.path.join('data', |
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70
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'benchmark', |
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filename)) |
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73
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74
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def prepare_word_pairs_file(src, dst, delimiter='\t'): |
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"""Transform formats of word pairs files to tsv.""" |
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df = pd.read_csv(src, header=None, delimiter=delimiter) |
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77
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df.loc[:, :2].to_csv(dst, sep=delimiter, index=False, header=False) |
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78
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79
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80
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def evaluate_word_pairs(model, kwargs_word_pairs=None): |
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81
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""" |
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Evaluate word pairs tasks. |
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83
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84
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:param model: Words embedding. |
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85
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:param kwargs_word_pairs: Kwargs for |
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86
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evaluate_word_pairs |
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method. |
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:type kwargs_word_pairs: dict or None |
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89
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:return: DataFrame of evaluation results. |
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90
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""" |
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91
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92
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if kwargs_word_pairs is None: |
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kwargs_word_pairs = {} |
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95
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results = {} |
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97
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for name, filename in WORD_PAIRS_TASKS.items(): |
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path = get_data_resource_path(filename) |
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(pearson, |
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spearman, |
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ratio_unknown_words) = model.evaluate_word_pairs(path, |
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**kwargs_word_pairs) # pylint: disable=C0301 |
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103
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104
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results[name] = {'pearson_r': pearson[0], |
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105
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'pearson_pvalue': pearson[1], |
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106
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'spearman_r': spearman.correlation, |
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'spearman_pvalue': spearman.pvalue, |
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108
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'ratio_unkonwn_words': ratio_unknown_words} |
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110
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df = (pd.DataFrame(results) |
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.reindex(PAIR_WORDS_EVALUATION_FIELDS) |
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.transpose() |
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113
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.round(3)) |
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114
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115
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return df |
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117
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118
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def evaluate_word_analogies(model, kwargs_word_analogies=None): |
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119
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""" |
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120
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Evaluate word analogies tasks. |
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121
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122
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:param model: Words embedding. |
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123
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:param kwargs_word_analogies: Kwargs for |
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evaluate_word_analogies |
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125
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method. |
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126
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:type evaluate_word_analogies: dict or None |
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127
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:return: DataFrame of evaluation results. |
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128
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""" |
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129
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130
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if kwargs_word_analogies is None: |
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kwargs_word_analogies = {} |
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133
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results = {} |
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134
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135
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for name, filename in ANALOGIES_TASKS.items(): |
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path = get_data_resource_path(filename) |
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overall_score, _ = model.evaluate_word_analogies(path, |
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**kwargs_word_analogies) # pylint: disable=C0301 |
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140
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results[name] = {'score': overall_score} |
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142
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df = (pd.DataFrame(results) |
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.transpose() |
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.round(3)) |
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146
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return df |
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147
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148
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149
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def evaluate_words_embedding(model, |
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kwargs_word_pairs=None, |
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kwargs_word_analogies=None): |
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152
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""" |
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153
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Evaluate word pairs tasks and word analogies tasks. |
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154
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155
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:param model: Words embedding. |
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156
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:param kwargs_word_pairs: Kwargs fo |
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157
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evaluate_word_pairs |
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158
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method. |
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159
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:type kwargs_word_pairs: dict or None |
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160
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:param kwargs_word_analogies: Kwargs for |
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evaluate_word_analogies |
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162
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method. |
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163
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:type evaluate_word_analogies: dict or None |
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164
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:return: Tuple of DataFrame for the evaluation results. |
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165
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""" |
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166
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return (evaluate_word_pairs(model, kwargs_word_pairs), |
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167
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evaluate_word_analogies(model, kwargs_word_analogies)) |
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168
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