Datasets:
Sub-tasks:
language-modeling
Languages:
English
Multilinguality:
multilingual
Size Categories:
10M<n<100M
Language Creators:
crowdsourced
Annotations Creators:
no-annotation
Tags:
text-search
License:
File size: 8,282 Bytes
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# WARNING: Please, do not use the code in this script as a template to create another script:
# - It is a bad practice to use `datasets.load_dataset` inside a loading script. Please, avoid doing it.
import json
import math
import datasets
logger = datasets.logging.get_logger(__name__)
_CITATION = """\
@ONLINE {wikidump,
author = {Wikimedia Foundation},
title = {Wikimedia Downloads},
url = {https://dumps.wikimedia.org}
}
"""
_DESCRIPTION = """\
Wikipedia version split into plain text snippets for dense semantic indexing.
"""
_LICENSE = (
"This work is licensed under the Creative Commons Attribution-ShareAlike "
"3.0 Unported License. To view a copy of this license, visit "
"http://creativecommons.org/licenses/by-sa/3.0/ or send a letter to "
"Creative Commons, PO Box 1866, Mountain View, CA 94042, USA."
)
def wiki40b_article_snippets(article, passage_len=100, overlap=0):
paragraphs = article["text"].split("\n")
aticle_idx = paragraphs.index("_START_ARTICLE_") + 1
article_title = paragraphs[aticle_idx] if aticle_idx < len(paragraphs) else ""
section_indices = [i + 1 for i, par in enumerate(paragraphs[:-1]) if par == "_START_SECTION_"]
par_tabs = [par.split(" ") for par in paragraphs]
word_map = [
(i, len(" ".join(par[:j])), w)
for i, par in enumerate(par_tabs)
if not par[0].startswith("_START_")
for j, w in enumerate(par)
if i > 0
]
step_size = passage_len - overlap
passages = []
for i in range(math.ceil(len(word_map) / step_size)):
pre_toks = word_map[i * step_size : i * step_size + passage_len]
start_section_id = max([0] + [j for j in section_indices if j <= pre_toks[0][0]])
section_ids = [j for j in section_indices if j >= start_section_id and j <= pre_toks[-1][0]]
section_ids = section_ids if len(section_ids) > 0 else [0]
passage_text = " ".join([w for p_id, s_id, w in pre_toks])
passages += [
{
"article_title": article_title,
"section_title": " & ".join([paragraphs[j] for j in section_ids]),
"wiki_id": article["wikidata_id"],
"start_paragraph": pre_toks[0][0],
"start_character": pre_toks[0][1],
"end_paragraph": pre_toks[-1][0],
"end_character": pre_toks[-1][1] + len(pre_toks[-1][2]) + 1,
"passage_text": passage_text.replace("_NEWLINE_", "\n"),
}
]
return passages
def wikipedia_article_snippets(article, passage_len=100, overlap=0):
paragraphs = [par for par in article["text"].split("\n") if not par.startswith("Category:")]
if "References" in paragraphs:
paragraphs = paragraphs[: paragraphs.index("References")]
article_title = article["title"]
section_indices = [
i + 1
for i, par in enumerate(paragraphs[:-2])
if paragraphs[i] == "" and paragraphs[i + 1] != "" and paragraphs[i + 2] != ""
]
par_tabs = [par.split(" ") for par in paragraphs]
word_map = [(i, len(" ".join(par[:j])), w) for i, par in enumerate(par_tabs) for j, w in enumerate(par)]
step_size = passage_len - overlap
passages = []
for i in range(math.ceil(len(word_map) / step_size)):
pre_toks = word_map[i * step_size : i * step_size + passage_len]
start_section_id = max([0] + [j for j in section_indices if j <= pre_toks[0][0]])
section_ids = [j for j in section_indices if start_section_id <= j <= pre_toks[-1][0]]
section_ids = section_ids if len(section_ids) > 0 else [-1]
passage_text = " ".join([w for p_id, s_id, w in pre_toks])
passages += [
{
"article_title": article_title,
"section_title": " & ".join(["Start" if j == -1 else paragraphs[j].strip() for j in section_ids]),
"wiki_id": article_title.replace(" ", "_"),
"start_paragraph": pre_toks[0][0],
"start_character": pre_toks[0][1],
"end_paragraph": pre_toks[-1][0],
"end_character": pre_toks[-1][1] + len(pre_toks[-1][2]) + 1,
"passage_text": passage_text,
}
]
return passages
_SPLIT_FUNCTION_MAP = {
"wikipedia": wikipedia_article_snippets,
"wiki40b": wiki40b_article_snippets,
}
def generate_snippets(wikipedia, split_function, passage_len=100, overlap=0):
for i, article in enumerate(wikipedia):
for doc in split_function(article, passage_len, overlap):
part_id = json.dumps(
{
"datasets_id": i,
"wiki_id": doc["wiki_id"],
"sp": doc["start_paragraph"],
"sc": doc["start_character"],
"ep": doc["end_paragraph"],
"ec": doc["end_character"],
}
)
doc["_id"] = part_id
doc["datasets_id"] = i
yield doc
class WikiSnippetsConfig(datasets.BuilderConfig):
"""BuilderConfig for WikiSnippets."""
def __init__(
self, wikipedia_name="wiki40b", wikipedia_version_name="en", snippets_length=100, snippets_overlap=0, **kwargs
):
"""BuilderConfig for WikiSnippets.
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(WikiSnippetsConfig, self).__init__(**kwargs)
self.wikipedia_name = wikipedia_name
self.wikipedia_version_name = wikipedia_version_name
self.snippets_length = snippets_length
self.snippets_overlap = snippets_overlap
class WikiSnippets(datasets.GeneratorBasedBuilder):
BUILDER_CONFIG_CLASS = WikiSnippetsConfig
BUILDER_CONFIGS = [
WikiSnippetsConfig(
name="wiki40b_en_100_0",
version=datasets.Version("1.0.0"),
wikipedia_name="wiki40b",
wikipedia_version_name="en",
snippets_length=100,
snippets_overlap=0,
),
WikiSnippetsConfig(
name="wikipedia_en_100_0",
version=datasets.Version("2.0.0"),
wikipedia_name="wikipedia",
wikipedia_version_name="20220301.en",
snippets_length=100,
snippets_overlap=0,
),
]
test_dummy_data = False
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"_id": datasets.Value("string"),
"datasets_id": datasets.Value("int32"),
"wiki_id": datasets.Value("string"),
"start_paragraph": datasets.Value("int32"),
"start_character": datasets.Value("int32"),
"end_paragraph": datasets.Value("int32"),
"end_character": datasets.Value("int32"),
"article_title": datasets.Value("string"),
"section_title": datasets.Value("string"),
"passage_text": datasets.Value("string"),
}
),
supervised_keys=None,
homepage="https://dumps.wikimedia.org",
citation=_CITATION,
)
def _split_generators(self, dl_manager):
# WARNING: It is a bad practice to use `datasets.load_dataset` inside a loading script. Please, avoid doing it.
wikipedia = datasets.load_dataset(
path=self.config.wikipedia_name,
name=self.config.wikipedia_version_name,
)
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"wikipedia": wikipedia}),
]
def _generate_examples(self, wikipedia):
logger.info(f"generating examples from = {self.config.wikipedia_name} {self.config.wikipedia_version_name}")
for split in wikipedia:
dset = wikipedia[split]
split_function = _SPLIT_FUNCTION_MAP[self.config.wikipedia_name]
for doc in generate_snippets(
dset, split_function, passage_len=self.config.snippets_length, overlap=self.config.snippets_overlap
):
id_ = doc["_id"]
yield id_, doc
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