Datasets:
Tasks:
Text Classification
Sub-tasks:
semantic-similarity-classification
Languages:
English
Size:
100K<n<1M
License:
| # coding=utf-8 | |
| # Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors. | |
| # | |
| # 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. | |
| # Lint as: python3 | |
| """Quora question pairs data""" | |
| import csv | |
| import datasets | |
| _DESCRIPTION = "The Quora dataset is composed of question pairs, and the task is to determine if the questions are paraphrases of each other (have the same meaning)." | |
| _URL = "http://qim.fs.quoracdn.net/quora_duplicate_questions.tsv" | |
| class Quora(datasets.GeneratorBasedBuilder): | |
| """Quora Question Pairs dataset""" | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=datasets.Features( | |
| { | |
| "questions": datasets.features.Sequence( | |
| { | |
| "id": datasets.Value("int32"), | |
| "text": datasets.Value("string"), | |
| } | |
| ), | |
| "is_duplicate": datasets.Value("bool"), | |
| } | |
| ), | |
| homepage="https://www.quora.com/q/quoradata/First-Quora-Dataset-Release-Question-Pairs", | |
| ) | |
| def _split_generators(self, dl_manager): | |
| data_file = dl_manager.download_and_extract({"data_file": _URL}) | |
| return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs=data_file)] | |
| def _generate_examples(self, data_file): | |
| with open(data_file, encoding="utf-8") as f: | |
| data = csv.DictReader(f, delimiter="\t") | |
| for idx, row in enumerate(data): | |
| yield idx, { | |
| "questions": [ | |
| {"id": row["qid1"], "text": row["question1"]}, | |
| {"id": row["qid2"], "text": row["question2"]}, | |
| ], | |
| "is_duplicate": row["is_duplicate"] == "1", | |
| } | |