File size: 2,176 Bytes
0bc91e1 f07159f 0bc91e1 f07159f 0bc91e1 f07159f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 |
import os
import json
from tqdm import tqdm
import numpy as np
from datasets import load_dataset
export_dir = 'dataset'
os.makedirs(export_dir, exist_ok=True)
dataset = load_dataset("conceptnet5", "conceptnet5", split="train")
def check(example):
if example['sentence'] == '':
return False
if example['lang'] != 'en':
return False
if example['rel'] == 'None':
return False
atom_1 = os.path.basename(example['arg1'])
atom_2 = os.path.basename(example['arg2'])
for atom in [atom_1, atom_2]:
if len(atom) <= 2: # condition on the number of characters
return False
if len(atom.split(' ')) != 1: # condition on the number of words
return False
if len(atom.split('_')) != 1: # condition on the number of words
return False
return True
dataset = dataset.filter(lambda example: check(example))
relations = list(set(dataset["rel"]))
all_word = [os.path.basename(i) for i in dataset['arg1'] + dataset['arg2']]
t, c = np.unique(all_word, return_counts=True)
freq = {_t: _c for _t, _c in zip(t, c)}
def freq_filter(example): # filter by entity frequency
if freq[os.path.basename(example['arg1'])] < 5:
return False
if freq[os.path.basename(example['arg2'])] < 5:
return False
return True
with open(f"{export_dir}/train.jsonl", 'w') as f_train:
with open(f"{export_dir}/valid.jsonl", 'w') as f_valid:
for r in tqdm(relations):
_dataset = dataset.filter(lambda example: example['rel'] == r).shuffle(0)
pairs = [[os.path.basename(i['arg1']), os.path.basename(i['arg2'])] for i in _dataset if freq_filter(i)]
train_size = int(len(_dataset) * 0.7)
f_train.write(json.dumps({
'relation_type': os.path.basename(r),
'positives': pairs[:train_size],
'negatives': []
}))
if len(pairs[train_size:]) > 0:
f_valid.write(json.dumps({
'relation_type': os.path.basename(r),
'positives': pairs[train_size:],
'negatives': []
}))
|