Datasets:
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"""FaQUAD-NLI dataset"""
import datasets
import pandas as pd
import json
_CITATION = """
"""
_DESCRIPTION = """
"""
_URLS = {
"data": "https://raw.githubusercontent.com/liafacom/faquad/6ad978f20672bb41625b3b71fbe4a88b893d0a86/data/dataset.json",
"spans": "https://huggingface.co/datasets/ruanchaves/faquad-nli/raw/main/spans.csv"
}
def check_overlap(interval1, interval2):
"""Check for overlap between two integer intervals"""
return not (interval1[1] < interval2[0] or interval2[1] < interval1[0])
class Faquad(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("1.0.0")
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"document_index": datasets.Value("int32"),
"document_title": datasets.Value("string"),
"paragraph_index": datasets.Value("int32"),
"question": datasets.Value("string"),
"answer": datasets.Value("string"),
"label": datasets.Value("int32")
}),
supervised_keys=None,
homepage="https://github.com/franciellevargas/HateBR",
citation=_CITATION,
)
def _split_generators(self, dl_manager):
downloaded_files = dl_manager.download(_URLS)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"data": downloaded_files["data"],
"spans": downloaded_files["spans"],
"split": "train"
}
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={
"data": downloaded_files["data"],
"spans": downloaded_files["spans"],
"split": "validation"
}
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"data": downloaded_files["data"],
"spans": downloaded_files["spans"],
"split": "test"
}
)
]
def _generate_examples(self, data, spans, split):
with open(data, 'r') as f:
json_data = json.load(f)
spans = pd.read_csv(spans).to_dict("records")
counter = 0
for span_row in spans:
if span_row["split"] != split:
continue
document_title = json_data["data"][
span_row["document_index"]
]["title"]
sentence = json_data["data"][
span_row["document_index"]
]["paragraphs"][
span_row["paragraph_index"]
]["context"][
span_row["sentence_start_char"]:span_row["sentence_end_char"]
]
sentence_interval = (span_row["sentence_start_char"], span_row["sentence_end_char"])
for qas_row in json_data["data"][
span_row["document_index"]
]["paragraphs"][
span_row["paragraph_index"]
]["qas"]:
question = qas_row["question"]
question_spans = []
for qas_answer in qas_row["answers"]:
qas_answer_start_span = qas_answer["answer_start"]
qas_answer_end_span = qas_answer["answer_start"] + len(qas_answer["text"])
question_spans.append((qas_answer_start_span, qas_answer_end_span))
for question_interval in question_spans:
if check_overlap(sentence_interval, question_interval):
yield counter, {
"document_index": span_row["document_index"],
"document_title": document_title,
"paragraph_index": span_row["paragraph_index"],
"question": question,
"answer": sentence,
"label": 1
}
counter += 1
break
else:
yield counter, {
"document_index": span_row["document_index"],
"document_title": document_title,
"paragraph_index": span_row["paragraph_index"],
"question": question,
"answer": sentence,
"label": 0
}
counter += 1 |