Spaces:
Runtime error
Runtime error
File size: 3,232 Bytes
d6585f5 |
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 64 65 66 67 68 69 70 71 72 73 74 |
#
# Pyserini: Reproducible IR research with sparse and dense representations
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import json
import argparse
from tqdm import tqdm
from nltk import bigrams, word_tokenize, SnowballStemmer
from nltk.corpus import stopwords
import string
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Convert KILT Knowledge Source into a Passage-level JSONL that can be processed by Pyserini')
parser.add_argument('--input', dest="input", required=True, help='Path to the kilt_knowledgesource.json file')
parser.add_argument('--output', dest="output", required=True, help='Path to the output directory and file name')
parser.add_argument('--bigrams', action='store_true', help='Enable bigrams')
parser.add_argument('--stem', action='store_true', help='Enable stemming on bigrams')
parser.add_argument('--sections', action='store_true', help='Split article by sections')
parser.add_argument('--flen', default=5903530, type=int, help='Number of lines in the file')
args = parser.parse_args()
FILE_LENGTH = args.flen
STOPWORDS = set(stopwords.words('english') + list(string.punctuation))
stemmer = SnowballStemmer("english")
with open(args.input, 'r') as f, open(f'{args.output}', 'w') as outp:
for line in tqdm(f, total=FILE_LENGTH, mininterval=10.0, maxinterval=20.0):
raw = json.loads(line)
texts = raw["text"]
if args.sections:
sections = [[]]
for i in range(1, len(texts)):
p = texts[i]
if p.startswith('Section::::'):
sections.append([])
sections[-1].append(p)
texts = [raw["text"][0]] + ["".join(s) for s in sections]
for i in range(1, len(texts)):
# The first passage is actually the wikipedia title
doc = {}
doc["id"] = f"{raw['_id']}-{i}"
p = texts[i]
if args.bigrams:
tokens = filter(lambda word: word.lower() not in STOPWORDS, word_tokenize(p))
if args.stem:
tokens = map(stemmer.stem, tokens)
bigram_doc = bigrams(tokens)
bigram_doc = " ".join(["".join(bigram) for bigram in bigram_doc])
p += " " + bigram_doc
doc["contents"] = raw["text"][0] + p
doc["wikipedia_id"] = raw["wikipedia_id"]
doc["wikipedia_title"] = raw["wikipedia_title"]
doc["categories"] = raw["categories"]
_ = outp.write(json.dumps(doc))
_ = outp.write('\n')
|