Convert dataset to Parquet

#2
by albertvillanova HF staff - opened
README.md CHANGED
@@ -43,16 +43,25 @@ dataset_info:
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  dtype: string
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  splits:
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  - name: train
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- num_bytes: 4778409
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  num_examples: 20000
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  - name: test
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- num_bytes: 493038
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  num_examples: 2120
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  - name: validation
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- num_bytes: 477964
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  num_examples: 2051
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- download_size: 8135045
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- dataset_size: 5749411
 
 
 
 
 
 
 
 
 
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  ---
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  # Dataset Card for Business Scene Dialogue
 
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  dtype: string
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  splits:
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  - name: train
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+ num_bytes: 4778291
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  num_examples: 20000
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  - name: test
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+ num_bytes: 492986
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  num_examples: 2120
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  - name: validation
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+ num_bytes: 477935
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  num_examples: 2051
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+ download_size: 1843443
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+ dataset_size: 5749212
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+ configs:
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+ - config_name: default
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+ data_files:
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+ - split: train
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+ path: data/train-*
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+ - split: test
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+ path: data/test-*
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+ - split: validation
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+ path: data/validation-*
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  ---
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  # Dataset Card for Business Scene Dialogue
bsd_ja_en.py DELETED
@@ -1,163 +0,0 @@
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- # coding=utf-8
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- # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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- #
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- # Licensed under the Apache License, Version 2.0 (the "License");
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- # you may not use this file except in compliance with the License.
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- # You may obtain a copy of the License at
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- #
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- # http://www.apache.org/licenses/LICENSE-2.0
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- #
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- # Unless required by applicable law or agreed to in writing, software
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- # distributed under the License is distributed on an "AS IS" BASIS,
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- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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- # See the License for the specific language governing permissions and
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- # limitations under the License.
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- """Japanese-English Business Scene Dialogue (BSD) dataset. """
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-
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-
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- import json
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-
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- import datasets
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-
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-
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- _CITATION = """\
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- @inproceedings{rikters-etal-2019-designing,
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- title = "Designing the Business Conversation Corpus",
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- author = "Rikters, Matīss and
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- Ri, Ryokan and
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- Li, Tong and
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- Nakazawa, Toshiaki",
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- booktitle = "Proceedings of the 6th Workshop on Asian Translation",
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- month = nov,
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- year = "2019",
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- address = "Hong Kong, China",
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- publisher = "Association for Computational Linguistics",
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- url = "https://www.aclweb.org/anthology/D19-5204",
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- doi = "10.18653/v1/D19-5204",
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- pages = "54--61"
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- }
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- """
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-
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-
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- _DESCRIPTION = """\
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- This is the Business Scene Dialogue (BSD) dataset,
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- a Japanese-English parallel corpus containing written conversations
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- in various business scenarios.
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-
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- The dataset was constructed in 3 steps:
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- 1) selecting business scenes,
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- 2) writing monolingual conversation scenarios according to the selected scenes, and
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- 3) translating the scenarios into the other language.
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-
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- Half of the monolingual scenarios were written in Japanese
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- and the other half were written in English.
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-
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- Fields:
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- - id: dialogue identifier
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- - no: sentence pair number within a dialogue
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- - en_speaker: speaker name in English
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- - ja_speaker: speaker name in Japanese
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- - en_sentence: sentence in English
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- - ja_sentence: sentence in Japanese
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- - original_language: language in which monolingual scenario was written
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- - tag: scenario
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- - title: scenario title
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- """
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-
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- _HOMEPAGE = "https://github.com/tsuruoka-lab/BSD"
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-
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- _LICENSE = "CC BY-NC-SA 4.0"
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-
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- _REPO = "https://raw.githubusercontent.com/tsuruoka-lab/BSD/master/"
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-
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- _URLs = {
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- "train": _REPO + "train.json",
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- "dev": _REPO + "dev.json",
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- "test": _REPO + "test.json",
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- }
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-
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-
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- class BsdJaEn(datasets.GeneratorBasedBuilder):
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- """Japanese-English Business Scene Dialogue (BSD) dataset."""
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-
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- VERSION = datasets.Version("1.0.0")
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-
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- def _info(self):
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- features = datasets.Features(
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- {
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- "id": datasets.Value("string"),
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- "tag": datasets.Value("string"),
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- "title": datasets.Value("string"),
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- "original_language": datasets.Value("string"),
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- "no": datasets.Value("int32"),
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- "en_speaker": datasets.Value("string"),
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- "ja_speaker": datasets.Value("string"),
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- "en_sentence": datasets.Value("string"),
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- "ja_sentence": datasets.Value("string"),
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- }
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- )
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- return datasets.DatasetInfo(
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- description=_DESCRIPTION,
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- features=features,
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- supervised_keys=None,
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- homepage=_HOMEPAGE,
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- license=_LICENSE,
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- citation=_CITATION,
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- )
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-
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- def _split_generators(self, dl_manager):
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- """Returns SplitGenerators."""
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- data_dir = dl_manager.download_and_extract(_URLs)
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-
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- return [
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- datasets.SplitGenerator(
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- name=datasets.Split.TRAIN,
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- gen_kwargs={
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- "filepath": data_dir["train"],
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- "split": "train",
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- },
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- ),
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- datasets.SplitGenerator(
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- name=datasets.Split.TEST,
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- gen_kwargs={"filepath": data_dir["test"], "split": "test"},
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- ),
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- datasets.SplitGenerator(
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- name=datasets.Split.VALIDATION,
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- gen_kwargs={
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- "filepath": data_dir["dev"],
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- "split": "dev",
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- },
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- ),
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- ]
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-
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- def _generate_examples(self, filepath, split):
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- """Yields examples."""
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-
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- with open(filepath, encoding="utf-8") as f:
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- data = json.load(f)
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-
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- for dialogue in data:
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- id_ = dialogue["id"]
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- tag = dialogue["tag"]
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- title = dialogue["title"]
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- original_language = dialogue["original_language"]
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- conversation = dialogue["conversation"]
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-
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- for turn in conversation:
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- sent_no = int(turn["no"])
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- en_speaker = turn["en_speaker"]
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- ja_speaker = turn["ja_speaker"]
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- en_sentence = turn["en_sentence"]
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- ja_sentence = turn["ja_sentence"]
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-
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- yield f"{id_}_{sent_no}", {
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- "id": id_,
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- "tag": tag,
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- "title": title,
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- "original_language": original_language,
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- "no": sent_no,
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- "en_speaker": en_speaker,
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- "ja_speaker": ja_speaker,
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- "en_sentence": en_sentence,
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- "ja_sentence": ja_sentence,
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- }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
data/test-00000-of-00001.parquet ADDED
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+ version https://git-lfs.github.com/spec/v1
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data/train-00000-of-00001.parquet ADDED
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data/validation-00000-of-00001.parquet ADDED
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dataset_infos.json DELETED
@@ -1 +0,0 @@
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- {"default": {"description": "This is the Business Scene Dialogue (BSD) dataset,\na Japanese-English parallel corpus containing written conversations\nin various business scenarios.\n\nThe dataset was constructed in 3 steps:\n 1) selecting business scenes,\n 2) writing monolingual conversation scenarios according to the selected scenes, and\n 3) translating the scenarios into the other language.\n\nHalf of the monolingual scenarios were written in Japanese\nand the other half were written in English.\n\nFields:\n- id: dialogue identifier\n- no: sentence pair number within a dialogue\n- en_speaker: speaker name in English\n- ja_speaker: speaker name in Japanese\n- en_sentence: sentence in English\n- ja_sentence: sentence in Japanese\n- original_language: language in which monolingual scenario was written\n- tag: scenario\n- title: scenario title\n", "citation": "@inproceedings{rikters-etal-2019-designing,\n title = \"Designing the Business Conversation Corpus\",\n author = \"Rikters, Mat\u012bss and\n Ri, Ryokan and\n Li, Tong and\n Nakazawa, Toshiaki\",\n booktitle = \"Proceedings of the 6th Workshop on Asian Translation\",\n month = nov,\n year = \"2019\",\n address = \"Hong Kong, China\",\n publisher = \"Association for Computational Linguistics\",\n url = \"https://www.aclweb.org/anthology/D19-5204\",\n doi = \"10.18653/v1/D19-5204\",\n pages = \"54--61\"\n}\n", "homepage": "https://github.com/tsuruoka-lab/BSD", "license": "CC BY-NC-SA 4.0", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "tag": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "original_language": {"dtype": "string", "id": null, "_type": "Value"}, "no": {"dtype": "int32", "id": null, "_type": "Value"}, "en_speaker": {"dtype": "string", "id": null, "_type": "Value"}, "ja_speaker": {"dtype": "string", "id": null, "_type": "Value"}, "en_sentence": {"dtype": "string", "id": null, "_type": "Value"}, "ja_sentence": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "bsd_ja_en", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 4778409, "num_examples": 20000, "dataset_name": "bsd_ja_en"}, "test": {"name": "test", "num_bytes": 493038, "num_examples": 2120, "dataset_name": "bsd_ja_en"}, "validation": {"name": "validation", "num_bytes": 477964, "num_examples": 2051, "dataset_name": "bsd_ja_en"}}, "download_checksums": {"https://raw.githubusercontent.com/tsuruoka-lab/BSD/master/train.json": {"num_bytes": 6740756, "checksum": "e011d1b02ed1acdbed5b677b54a3ceae26baaf6cd2a4fea64e4af4ff699c5ffb"}, "https://raw.githubusercontent.com/tsuruoka-lab/BSD/master/dev.json": {"num_bytes": 687409, "checksum": "43c11e7d9bdb4ab8ecc83114c82a77c596f98c8845af92fb74c8ca12cc9cfa5c"}, "https://raw.githubusercontent.com/tsuruoka-lab/BSD/master/test.json": {"num_bytes": 706880, "checksum": "9da3f8907147b2424671058c93d9f41179ddbd8d0c8298a3e8546c2703174d31"}}, "download_size": 8135045, "post_processing_size": null, "dataset_size": 5749411, "size_in_bytes": 13884456}}