Convert dataset to Parquet

#4
by albertvillanova HF staff - opened
README.md CHANGED
@@ -20,6 +20,7 @@ task_ids:
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  paperswithcode_id: definite-pronoun-resolution-dataset
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  pretty_name: Definite Pronoun Resolution Dataset
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  dataset_info:
 
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  features:
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  - name: sentence
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  dtype: string
@@ -34,16 +35,23 @@ dataset_info:
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  names:
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  '0': '0'
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  '1': '1'
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- config_name: plain_text
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  splits:
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  - name: test
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- num_bytes: 71691
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  num_examples: 564
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  - name: train
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- num_bytes: 171511
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  num_examples: 1322
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- download_size: 227452
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- dataset_size: 243202
 
 
 
 
 
 
 
 
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  ---
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  # Dataset Card for "definite_pronoun_resolution"
 
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  paperswithcode_id: definite-pronoun-resolution-dataset
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  pretty_name: Definite Pronoun Resolution Dataset
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  dataset_info:
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+ config_name: plain_text
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  features:
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  - name: sentence
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  dtype: string
 
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  names:
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  '0': '0'
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  '1': '1'
 
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  splits:
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  - name: test
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+ num_bytes: 71679
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  num_examples: 564
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  - name: train
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+ num_bytes: 171499
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  num_examples: 1322
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+ download_size: 106997
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+ dataset_size: 243178
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+ configs:
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+ - config_name: plain_text
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+ data_files:
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+ - split: test
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+ path: plain_text/test-*
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+ - split: train
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+ path: plain_text/train-*
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+ default: true
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  ---
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  # Dataset Card for "definite_pronoun_resolution"
definite_pronoun_resolution.py DELETED
@@ -1,105 +0,0 @@
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- # coding=utf-8
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- # Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
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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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-
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- # Lint as: python3
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- """The Definite Pronoun Resolution Dataset."""
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-
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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{rahman2012resolving,
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- title={Resolving complex cases of definite pronouns: the winograd schema challenge},
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- author={Rahman, Altaf and Ng, Vincent},
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- booktitle={Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning},
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- pages={777--789},
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- year={2012},
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- organization={Association for Computational Linguistics}
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- }"""
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-
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- _DESCRIPTION = """\
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- Composed by 30 students from one of the author's undergraduate classes. These
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- sentence pairs cover topics ranging from real events (e.g., Iran's plan to
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- attack the Saudi ambassador to the U.S.) to events/characters in movies (e.g.,
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- Batman) and purely imaginary situations, largely reflecting the pop culture as
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- perceived by the American kids born in the early 90s. Each annotated example
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- spans four lines: the first line contains the sentence, the second line contains
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- the target pronoun, the third line contains the two candidate antecedents, and
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- the fourth line contains the correct antecedent. If the target pronoun appears
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- more than once in the sentence, its first occurrence is the one to be resolved.
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- """
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-
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-
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- _DATA_URL_PATTERN = "https://s3.amazonaws.com/datasets.huggingface.co/definite_pronoun_resolution/{}.c.txt"
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-
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-
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- class DefinitePronounResolution(datasets.GeneratorBasedBuilder):
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- """The Definite Pronoun Resolution Dataset."""
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-
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- BUILDER_CONFIGS = [
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- datasets.BuilderConfig(
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- name="plain_text",
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- version=datasets.Version("1.0.0", ""),
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- description="Plain text import of the Definite Pronoun Resolution Dataset.", # pylint: disable=line-too-long
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- )
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- ]
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-
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- def _info(self):
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- return datasets.DatasetInfo(
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- description=_DESCRIPTION,
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- features=datasets.Features(
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- {
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- "sentence": datasets.Value("string"),
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- "pronoun": datasets.Value("string"),
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- "candidates": datasets.features.Sequence(datasets.Value("string"), length=2),
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- "label": datasets.features.ClassLabel(num_classes=2),
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- }
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- ),
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- supervised_keys=("sentence", "label"),
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- homepage="http://www.hlt.utdallas.edu/~vince/data/emnlp12/",
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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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- files = dl_manager.download_and_extract(
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- {
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- "train": _DATA_URL_PATTERN.format("train"),
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- "test": _DATA_URL_PATTERN.format("test"),
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- }
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- )
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- return [
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- datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": files["test"]}),
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- datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": files["train"]}),
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- ]
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-
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- def _generate_examples(self, filepath):
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- with open(filepath, encoding="utf-8") as f:
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- line_num = -1
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- while True:
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- line_num += 1
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- sentence = f.readline().strip()
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- pronoun = f.readline().strip()
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- candidates = [c.strip() for c in f.readline().strip().split(",")]
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- correct = f.readline().strip()
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- f.readline()
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- if not sentence:
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- break
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- yield line_num, {
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- "sentence": sentence,
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- "pronoun": pronoun,
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- "candidates": candidates,
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- "label": candidates.index(correct),
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- }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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plain_text/train-00000-of-00001.parquet ADDED
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