init

get_stats.py

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+import pandas as pd
+from datasets import load_dataset
+
+data = load_dataset('relbert/conceptnet_high_confidence')
+stats = []
+for k in data.keys():
+    for i in data[k]:
+        stats.append({'relation_type': i['relation_type'], 'split': k, 'positives': len(i['positives']), 'negatives': len(i['negatives'])})
+df = pd.DataFrame(stats)
+df_train = df[df['split'] == 'train']
+df_valid = df[df['split'] == 'validation']
+stats = []
+for r in df['relation_type'].unique():
+    _df_t = df_train[df_train['relation_type'] == r]
+    _df_v = df_valid[df_valid['relation_type'] == r]
+    stats.append({
+        'relation_type': r,
+        'positive (train)': 0 if len(_df_t) == 0 else _df_t['positives'].values[0],
+        'negative (train)': 0 if len(_df_t) == 0 else _df_t['negatives'].values[0],
+        'positive (validation)': 0 if len(_df_v) == 0 else _df_v['positives'].values[0],
+        'negative (validation)': 0 if len(_df_v) == 0 else _df_v['negatives'].values[0],
+    })
+
+df = pd.DataFrame(stats).sort_values(by=['relation_type'])
+df.to_csv('stats.csv', index=None)
+
+

stats.csv

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+relation_type,positive (train),negative (train),positive (validation),negative (validation)
+AtLocation,383,356,97,80
+CapableOf,195,190,73,78
+Causes,71,73,26,26
+CausesDesire,9,7,11,11
+CreatedBy,2,3,1,1
+DefinedAs,1,1,2,2
+Desires,16,15,12,12
+HasA,67,86,17,17
+HasFirstSubevent,2,3,1,1
+HasLastSubevent,2,3,3,1
+HasPrerequisite,168,176,57,54
+HasProperty,94,100,39,49
+HasSubevent,125,128,40,54
+IsA,310,279,98,106
+MadeOf,17,15,7,5
+MotivatedByGoal,14,15,11,11
+NotCapableOf,15,13,1,1
+NotDesires,4,4,4,1
+NotHasProperty,1,3,1,1
+NotIsA,1,0,1,1
+NotMadeOf,1,3,0,0
+PartOf,34,40,7,5
+ReceivesAction,18,16,8,6
+RelatedTo,1,2,0,0
+SymbolOf,0,0,2,3
+UsedFor,249,269,81,74