Update unify_predicate.py

unify_predicate.py

@@ -1,15 +1,3 @@
-# import json
-# import pandas as pd
-#
-# with open("data/t_rex.filter.jsonl") as f:
-#     data = pd.DataFrame([json.loads(i) for i in f.read().split('\n') if len(i) > 0])
-# freq = data.groupby("predicate").count()['title']
-# data['freq'] = [freq.loc[i] for i in data['predicate']]
-# data = data[data['freq'] >= 3]
-# tmp = data.groupby("predicate").sample(10, replace=True)
-# tmp = tmp.drop_duplicates()
-# tmp.to_csv("data/t_rex.filter.predicate_check_sample.csv", index=False)
-
 import json
 import pandas as pd
 
@@ -59,11 +47,8 @@ data_filter_join.pop("reverse")
 data_filter_join.pop("predicate")
 data_filter_join['predicate'] = data_filter_join.pop("pretty relation name")
 
-print(f"[after] : {len(data_filter_join)}")
-print(f"[entity]: {len(set(data_filter_join['object'].unique().tolist() + data_filter_join['subject'].unique().tolist()))}")
-print(f"[predicate]: {len(data_filter_join['predicate'].unique())}")
-
+print(f"{len(data_filter_join)} triples, {len(data_filter_join['predicate'].unique())} predicates")
 
-data = [i.to_dict() for _, i in data_filter_join.iterrows()]
 with open(f"data/t_rex.filter_unified.jsonl", 'w') as f:
-    f.write('\n'.join([json.dumps(i) for i in data]))
+    for _, i in data_filter_join.iterrows():
+        f.write(json.dumps(i) + '\n')