unify_predicate.py

# 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

# load manual check sheet
df_predicate = pd.read_csv('predicate_manual_check.csv')
df_predicate = df_predicate[df_predicate['remove (noisy)'] != 'x']
df_predicate = df_predicate[df_predicate['remove (too vague)'] != 'x']
predicate_main = df_predicate[df_predicate['ok'] == 'x']['unique predicates'].tolist()
df_sub = df_predicate[df_predicate['ok'] != 'x']
df_sub_same = df_sub[['unique predicates', 'same as']].dropna()
df_sub_same = df_sub_same[[i in predicate_main for i in df_sub_same['same as']]]
df_sub_same.index = df_sub_same.pop('unique predicates')
sub_same = df_sub_same['same as'].to_dict()
df_sub_rev = df_sub[['unique predicates', 'reverse of']].dropna()
df_sub_rev = df_sub_rev[[i in predicate_main for i in df_sub_rev['reverse of']]]
df_sub_rev.index = df_sub_rev.pop('unique predicates')
sub_rev = df_sub_rev['reverse of'].to_dict()

# load data and filter based on manual predicate check sheet
with open(f"data/t_rex.filter.jsonl") as f:
    data = pd.DataFrame([json.loads(i) for i in f.read().split('\n') if len(i) > 0])
data['predicate'] = [sub_same[i] if i in sub_same else i for i in data['predicate']]
data['reverse'] = [i in sub_rev for i in data['predicate']]
data['predicate'] = [sub_rev[i] if i in sub_rev else i for i in data['predicate']]
data_filter = data[[i in predicate_main for i in data['predicate']]]

data_filter_rev = data_filter[data_filter['reverse']].copy()
o = data_filter_rev.pop("object")
s = data_filter_rev.pop("subject")
data_filter_rev["subject"] = o
data_filter_rev["object"] = s
data_filter[data_filter['reverse']] = data_filter_rev[data_filter.columns]
data_filter.pop("reverse")

df_main = df_predicate[df_predicate['ok'] == 'x'][['unique predicates', 'pretty relation name', 'pretty relation name is reverse']]
df_main['reverse'] = [i == 'x' for i in df_main.pop('pretty relation name is reverse')]
df_main['predicate'] = df_main.pop('unique predicates')

data_filter_join = data_filter.merge(df_main, how='inner', on='predicate')
data_filter_join_rev = data_filter_join[data_filter_join['reverse']].copy()
o = data_filter_join_rev.pop("object")
s = data_filter_join_rev.pop("subject")
data_filter_join_rev["subject"] = o
data_filter_join_rev["object"] = s
data_filter_join[data_filter_join['reverse']] = data_filter_join_rev[data_filter_join.columns]
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())}")


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]))