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