| """ Process raw T-Rex file. |
| mkdir data_raw |
| cd data_raw |
| wget https://figshare.com/ndownloader/files/8760241 |
| unzip 8760241 |
| cd ../ |
| """ |
|
|
| import json |
| import string |
| import re |
| import os |
| from glob import glob |
| from tqdm import tqdm |
|
|
| import pandas as pd |
|
|
| |
| if not os.path.exists('data/t_rex.raw.jsonl'): |
| os.makedirs('data', exist_ok=True) |
| f_writer = open('data/t_rex.raw.jsonl', 'w') |
| for i in tqdm(glob("data_raw/*.json")): |
| with open(i) as f: |
| data = json.load(f) |
| for _data in data: |
| for triple in _data['triples']: |
| p = triple['predicate']['surfaceform'] |
| if p is None: |
| p = os.path.basename(triple['predicate']['uri']) |
| o = triple['object']['surfaceform'] |
| s = triple['subject']['surfaceform'] |
| if o is None or s is None: |
| input(triple) |
| out = {"predicate": p, "object": o, "subject": s, "title": _data["title"], "text": _data["text"]} |
| f_writer.write(json.dumps(out) + "\n") |
| f_writer.close() |
|
|
| |
| stopwords = ["he", "she", "they", "it"] |
| list_alnum = string.ascii_lowercase + '0123456789 ' |
|
|
|
|
| def filtering(entry): |
|
|
| def _subfilter(token): |
| if len(re.findall(rf'[^{list_alnum}]+', token)) != 0: |
| return False |
| if token in stopwords: |
| return False |
| if token.startswith("www"): |
| return False |
| if token.startswith("."): |
| return False |
| if token.startswith(","): |
| return False |
| if token.startswith("$"): |
| return False |
| if token.startswith("+"): |
| return False |
| if token.startswith("#"): |
| return False |
| return True |
|
|
| if not _subfilter(entry["object"].lower()): |
| return False |
| if not _subfilter(entry["subject"].lower()): |
| return False |
|
|
| if entry['object'].islower() and entry['subject'].islower(): |
| return False |
|
|
| return True |
|
|
|
|
| with open(f"data/t_rex.raw.jsonl") as f: |
| data = [json.loads(i) for i in f.read().split('\n') if len(i) > 0] |
| print(f"[raw dataset]: {len(data)} triples, {len(set([i['predicate'] for i in data]))} predicates") |
| data = [i for i in data if filtering(i)] |
| df = pd.DataFrame(data) |
| df = df.drop_duplicates() |
| print(f"[entity only] : {len(df)} triples, {len(df['predicate'].unique())} predicates") |
| count = df.groupby("predicate")['title'].count() |
| df = df[[count[p] >= 3 for p in df['predicate']]] |
| print(f"[remove rare predicate] : {len(df)} triples, {len(df['predicate'].unique())} predicates") |
|
|
| with open(f"data/t_rex.filter.jsonl", 'w') as f: |
| for _, i in df.iterrows(): |
| f.write(json.dumps(i.to_dict()) + '\n') |
|
|
