process.py

"""
- Wiki-One https://sites.cs.ucsb.edu/~xwhan/datasets/wiki.tar.gz
- NELL-One https://sites.cs.ucsb.edu/~xwhan/datasets/nell.tar.gz

wget https://sites.cs.ucsb.edu/~xwhan/datasets/nell.tar.gz
tar -xzf nell.tar.gz

wget https://sites.cs.ucsb.edu/~xwhan/datasets/wiki.tar.gz
tar -xzf wiki.tar.gz

"""
import os
import json
import re
from itertools import chain

data_dir_nell = "NELL"
data_dir_wiki = "Wiki"
os.makedirs("data", exist_ok=True)

short = ['alcs', "uk", "us", "usa", "npr", "nbc", "bbc", "cnn", "abc", "cbs", "nfl", "mlb", "nba", "nhl", "pga", "ncaa",
         "wjhu", "pbs", "un"]
non_entity_types = [
    'academicfield',
    'agent',
    'agriculturalproduct',
    'amphibian',
    'animal',
    'aquarium',
    'arachnid',
    'architect',
    'arthropod',
    'bakedgood',
    'bathroomitem',
    'bedroomitem',
    'beverage',
    'bird',
    'blog',
    'bodypart',
    'bone',
    'candy',
    'cave',
    'chemical',
    'clothing',
    'coffeedrink',
    'condiment',
    'crimeorcharge',
    'crustacean',
    'date',
    'dateliteral',
    'economicsector',
    'fish',
    'food',
    'fruit',
    'fungus',
    'furniture',
    'grain',
    'hallwayitem',
    'hobby',
    'insect',
    'invertebrate',
    'jobposition',
    'kitchenitem',
    'landscapefeatures',
    'legume',
    'location',
    'mammal',
    'meat',
    'mlsoftware',
    'mollusk',
    'month',
    'nut',
    'officebuildingroom',
    'physiologicalcondition',
    'plant',
    'politicsissue',
    'profession',
    'professionalorganization',
    'reptile',
    'room',
    'sport',
    'tableitem',
    'tradeunion',
    'vegetable',
    'vehicle',
    'vertebrate',
    'weapon',
    'wine'
]


def clean(token):
    _, _type, token = token.split(":")
    token = token.replace("_", " ")
    token = token.replace("__", "")
    token = re.sub(r"00\d\Z", "", token)
    token = re.sub(r"\An(\d+)", r"\1", token)
    if _type in non_entity_types:
        return token, _type
    new_token = []
    for _t in token.split(" "):
        if len(_t) == 0:
            continue
        if _t in short:
            _t = _t.upper()
        else:
            _t = _t.capitalize()
        new_token.append(_t)
    return " ".join(new_token), _type


if not os.path.exists(data_dir_nell):
    raise ValueError("Please download the dataset first\n"
                     "wget https://sites.cs.ucsb.edu/~xwhan/datasets/nell.tar.gz\n"
                     "tar -xzf nell.tar.gz")

if not os.path.exists(data_dir_wiki):
    raise ValueError("Please download the dataset first\n"
                     "wget https://sites.cs.ucsb.edu/~xwhan/datasets/wiki.tar.gz\n"
                     "tar -xzf wiki.tar.gz")


def read_file(_file):
    with open(_file, 'r') as f_reader:
        tmp = json.load(f_reader)
    flatten = list(chain(*[[{"relation": r, "head": h, "tail": t} for (h, r, t) in v] for v in tmp.values()]))
    # flatten = {}
    # for k, v in tmp.items():
    #     flatten[k] = [{"relation": r, "head": h, "tail": t} for (h, r, t) in v]
    return flatten


def read_vocab(_file):
    with open(_file) as f_reader:
        ent2ids = json.load(f_reader)
    return sorted(list(ent2ids.keys()))


if __name__ == '__main__':
    vocab = read_vocab(f"{data_dir_nell}/ent2ids")
    with open("data/nell.vocab.txt", 'w') as f:
        f.write("\n".join(vocab))
    vocab_clean = [clean(i)[0] if len(i.split(":")) > 2 else i for i in vocab]
    with open("data/nell.vocab.clean.txt", 'w') as f:
        f.write("\n".join(vocab_clean))

    vocab = read_vocab(f"{data_dir_wiki}/ent2ids")
    with open("data/wiki.vocab.txt", 'w') as f:
        f.write("\n".join(vocab))

    for i, s in zip(['dev_tasks.json', 'test_tasks.json', 'train_tasks.json'], ['validation', 'test', 'train']):
        d = read_file(f"{data_dir_nell}/{i}")
        for _d in d:
            head_entity, head_type = clean(_d['head'])
            _d['head_entity'] = head_entity
            _d['head_type'] = head_type

            tail_entity, tail_type = clean(_d['tail'])
            _d['tail_entity'] = tail_entity
            _d['tail_type'] = tail_type

        with open(f"data/nell.{s}.jsonl", "w") as f:
            f.write("\n".join([json.dumps(_d) for _d in d]))

        d = read_file(f"{data_dir_wiki}/{i}")
        for _d in d:
            _d['head_entity'] = ''
            _d['head_type'] = ''
            _d['tail_entity'] = ''
            _d['tail_type'] = ''
        with open(f"data/wiki.{s}.jsonl", "w") as f:
            f.write("\n".join([json.dumps(_d) for _d in d]))