fix readme

README.md

@@ -9,7 +9,7 @@ size_categories:
 - 1K<n<10K
 pretty_name: ConceptNet with High Confidence
 ---
-# Dataset Card for "relbert/conceptnet_high_confidence"
+# Dataset Card for "relbert/conceptnet_relation_similarity"
 ## Dataset Description
 - **Repository:** [RelBERT](https://github.com/asahi417/relbert)
 - **Paper:** [https://home.ttic.edu/~kgimpel/commonsense.html](https://home.ttic.edu/~kgimpel/commonsense.html)
@@ -19,6 +19,12 @@ pretty_name: ConceptNet with High Confidence
 The selected subset of ConceptNet used in [this work](https://home.ttic.edu/~kgimpel/commonsense.html), which compiled 
 to fine-tune [RelBERT](https://github.com/asahi417/relbert) model.
 We removed `NotCapableOf` and `NotDesires` to keep the positive relation only.
+We consider the original test set as test set, dev1 as the training set, and dev2 as the validation set.
+
+|train|validation|test|
+|--------:|----:|---------:|
+|15| 17 |      15|
+
 
 ## Dataset Structure
 ### Data Instances
@@ -31,36 +37,7 @@ An example of `train` looks as follows.
 }
 ```
 
-### Data Splits
-|  name   |train|validation|
-|---------|----:|---------:|
-|conceptnet_high_confidence| 25 |      24|
-
-### Number of Positive/Negative Word-pairs in each Split
 
-| relation_type    |   positive (train) |   negative (train) |   positive (validation) |   negative (validation) |
-|:-----------------|-------------------:|-------------------:|------------------------:|------------------------:|
-| AtLocation       |                383 |               1749 |                      97 |                     574 |
-| CapableOf        |                195 |               1771 |                      73 |                     596 |
-| Causes           |                 71 |               1778 |                      26 |                     591 |
-| CausesDesire     |                  9 |               1774 |                      11 |                     591 |
-| CreatedBy        |                  2 |               1777 |                       0 |                       0 |
-| DefinedAs        |                  0 |                  0 |                       2 |                     591 |
-| Desires          |                 16 |               1775 |                      12 |                     591 |
-| HasA             |                 67 |               1795 |                      17 |                     591 |
-| HasFirstSubevent |                  2 |               1777 |                       0 |                       0 |
-| HasLastSubevent  |                  2 |               1777 |                       3 |                     589 |
-| HasPrerequisite  |                168 |               1784 |                      57 |                     588 |
-| HasProperty      |                 94 |               1782 |                      39 |                     601 |
-| HasSubevent      |                125 |               1779 |                      40 |                     605 |
-| IsA              |                310 |               1745 |                      98 |                     599 |
-| MadeOf           |                 17 |               1774 |                       7 |                     589 |
-| MotivatedByGoal  |                 14 |               1777 |                      11 |                     591 |
-| PartOf           |                 34 |               1782 |                       7 |                     589 |
-| ReceivesAction   |                 18 |               1774 |                       8 |                     589 |
-| SymbolOf         |                  0 |                  0 |                       2 |                     592 |
-| UsedFor          |                249 |               1796 |                      81 |                     584 |
-| SUM              |               1776 |              31966 |                     591 |                   10641 |
 
 ### Citation Information
 ```

conceptnet_high_confidence.py → conceptnet_relation_similarity.py

@@ -3,8 +3,8 @@ import datasets
 
 logger = datasets.logging.get_logger(__name__)
 _DESCRIPTION = """[ConceptNet with high confidence](https://home.ttic.edu/~kgimpel/commonsense.html)"""
-_NAME = "conceptnet_high_confidence"
-_VERSION = "2.0.1"
+_NAME = "conceptnet_relation_similarity"
+_VERSION = "2.0.2"
 _CITATION = """
 @inproceedings{li-16,
 title = {Commonsense Knowledge Base Completion},
@@ -37,7 +37,7 @@ _URLS = {
 }
 
 
-class ConceptNetHighConfidenceConfig(datasets.BuilderConfig):
+class ConceptNetRelationSimilarityConfig(datasets.BuilderConfig):
     """BuilderConfig"""
 
     def __init__(self, **kwargs):
@@ -45,14 +45,14 @@ class ConceptNetHighConfidenceConfig(datasets.BuilderConfig):
         Args:
           **kwargs: keyword arguments forwarded to super.
         """
-        super(ConceptNetHighConfidenceConfig, self).__init__(**kwargs)
+        super(ConceptNetRelationSimilarityConfig, self).__init__(**kwargs)
 
 
-class ConceptNetHighConfidence(datasets.GeneratorBasedBuilder):
+class ConceptNetRelationSimilarity(datasets.GeneratorBasedBuilder):
     """Dataset."""
 
     BUILDER_CONFIGS = [
-        ConceptNetHighConfidenceConfig(name=_NAME, version=datasets.Version(_VERSION), description=_DESCRIPTION),
+        ConceptNetRelationSimilarityConfig(name=_NAME, version=datasets.Version(_VERSION), description=_DESCRIPTION),
     ]
 
     def _split_generators(self, dl_manager):

get_stats.py

@@ -1,35 +0,0 @@
-import pandas as pd
-from datasets import load_dataset
-
-data = load_dataset('relbert/conceptnet_high_confidence_v2')
-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.index = df.pop('relation_type')
-sum_pairs = df.sum(0)
-df = df.T
-df['SUM'] = sum_pairs
-df = df.T
-
-df.to_csv('stats.csv')
-with open('stats.md', 'w') as f:
-    f.write(df.to_markdown())
-
-

process.py

@@ -20,12 +20,12 @@ def wget(url, cache_dir: str = './cache'):
     path = f'{cache_dir}/{filename}'
     if os.path.exists(path):
         return path.replace('.gz', '')
-    with open(path, "wb") as f:
+    with open(path, "wb") as f_:
         r = requests.get(url)
-        f.write(r.content)
-    with gzip.open(path, 'rb') as f:
+        f_.write(r.content)
+    with gzip.open(path, 'rb') as f_:
         with open(path.replace('.gz', ''), 'wb') as f_write:
-            f_write.write(f.read())
+            f_write.write(f_.read())
     os.remove(path)
     return path.replace('.gz', '')
 
@@ -44,23 +44,35 @@ def read_file(file_name):
 if __name__ == '__main__':
     test_p, test_n = read_file(wget(urls['test']))
     dev1_p, dev1_n = read_file(wget(urls['dev1']))
-    train_p = pd.concat([test_p, dev1_p])
-    train_n = pd.concat([test_n, dev1_n])
+    dev2_p, dev2_n = read_file(wget(urls['dev2']))
+
+    with open(f'dataset/test.jsonl', 'w') as f:
+        for relation, df_p in test_p.groupby('relation'):
+            if len(df_p) < 2:
+                continue
+            if relation in exclude:
+                continue
+            df_n = test_n[test_n['relation'] == relation]
+            f.write(json.dumps({
+                'relation_type': relation,
+                'positives': df_p[['head', 'tail']].to_numpy().tolist(),
+                'negatives': df_n[['head', 'tail']].to_numpy().tolist()
+            }) + '\n')
+
     with open(f'dataset/train.jsonl', 'w') as f:
-        for relation, df_p in train_p.groupby('relation'):
+        for relation, df_p in dev1_p.groupby('relation'):
             if len(df_p) < 2:
                 continue
             if relation in exclude:
                 continue
             print(relation)
-            df_n = train_n[train_n['relation'] == relation]
+            df_n = dev1_n[dev1_n['relation'] == relation]
             f.write(json.dumps({
                 'relation_type': relation,
                 'positives': df_p[['head', 'tail']].to_numpy().tolist(),
                 'negatives': df_n[['head', 'tail']].to_numpy().tolist()
             }) + '\n')
 
-    dev2_p, dev2_n = read_file(wget(urls['dev2']))
     with open(f'dataset/valid.jsonl', 'w') as f:
         for relation, df_p in dev2_p.groupby('relation'):
             if len(df_p) < 2:

stats.csv

@@ -1,22 +0,0 @@
-relation_type,positive (train),negative (train),positive (validation),negative (validation)
-AtLocation,383,1749,97,574
-CapableOf,195,1771,73,596
-Causes,71,1778,26,591
-CausesDesire,9,1774,11,591
-CreatedBy,2,1777,0,0
-DefinedAs,0,0,2,591
-Desires,16,1775,12,591
-HasA,67,1795,17,591
-HasFirstSubevent,2,1777,0,0
-HasLastSubevent,2,1777,3,589
-HasPrerequisite,168,1784,57,588
-HasProperty,94,1782,39,601
-HasSubevent,125,1779,40,605
-IsA,310,1745,98,599
-MadeOf,17,1774,7,589
-MotivatedByGoal,14,1777,11,591
-PartOf,34,1782,7,589
-ReceivesAction,18,1774,8,589
-SymbolOf,0,0,2,592
-UsedFor,249,1796,81,584
-SUM,1776,31966,591,10641

stats.md

@@ -1,23 +0,0 @@
-| relation_type    |   positive (train) |   negative (train) |   positive (validation) |   negative (validation) |
-|:-----------------|-------------------:|-------------------:|------------------------:|------------------------:|
-| AtLocation       |                383 |               1749 |                      97 |                     574 |
-| CapableOf        |                195 |               1771 |                      73 |                     596 |
-| Causes           |                 71 |               1778 |                      26 |                     591 |
-| CausesDesire     |                  9 |               1774 |                      11 |                     591 |
-| CreatedBy        |                  2 |               1777 |                       0 |                       0 |
-| DefinedAs        |                  0 |                  0 |                       2 |                     591 |
-| Desires          |                 16 |               1775 |                      12 |                     591 |
-| HasA             |                 67 |               1795 |                      17 |                     591 |
-| HasFirstSubevent |                  2 |               1777 |                       0 |                       0 |
-| HasLastSubevent  |                  2 |               1777 |                       3 |                     589 |
-| HasPrerequisite  |                168 |               1784 |                      57 |                     588 |
-| HasProperty      |                 94 |               1782 |                      39 |                     601 |
-| HasSubevent      |                125 |               1779 |                      40 |                     605 |
-| IsA              |                310 |               1745 |                      98 |                     599 |
-| MadeOf           |                 17 |               1774 |                       7 |                     589 |
-| MotivatedByGoal  |                 14 |               1777 |                      11 |                     591 |
-| PartOf           |                 34 |               1782 |                       7 |                     589 |
-| ReceivesAction   |                 18 |               1774 |                       8 |                     589 |
-| SymbolOf         |                  0 |                  0 |                       2 |                     592 |
-| UsedFor          |                249 |               1796 |                      81 |                     584 |
-| SUM              |               1776 |              31966 |                     591 |                   10641 |