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README.md

@@ -1,211 +0,0 @@
----
-annotations_creators:
-- expert-generated
-language_creators:
-- crowdsourced
-language:
-- en
-license:
-- unknown
-multilinguality:
-- monolingual
-size_categories:
-- 1K<n<10K
-source_datasets:
-- original
-task_categories:
-- token-classification
-task_ids:
-- word-sense-disambiguation
-paperswithcode_id: definite-pronoun-resolution-dataset
-pretty_name: Definite Pronoun Resolution Dataset
-dataset_info:
-  features:
-  - name: sentence
-    dtype: string
-  - name: pronoun
-    dtype: string
-  - name: candidates
-    sequence: string
-    length: 2
-  - name: label
-    dtype:
-      class_label:
-        names:
-          '0': '0'
-          '1': '1'
-  config_name: plain_text
-  splits:
-  - name: test
-    num_bytes: 71691
-    num_examples: 564
-  - name: train
-    num_bytes: 171511
-    num_examples: 1322
-  download_size: 227452
-  dataset_size: 243202
----
-
-# Dataset Card for "definite_pronoun_resolution"
-
-## Table of Contents
-- [Dataset Description](#dataset-description)
-  - [Dataset Summary](#dataset-summary)
-  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
-  - [Languages](#languages)
-- [Dataset Structure](#dataset-structure)
-  - [Data Instances](#data-instances)
-  - [Data Fields](#data-fields)
-  - [Data Splits](#data-splits)
-- [Dataset Creation](#dataset-creation)
-  - [Curation Rationale](#curation-rationale)
-  - [Source Data](#source-data)
-  - [Annotations](#annotations)
-  - [Personal and Sensitive Information](#personal-and-sensitive-information)
-- [Considerations for Using the Data](#considerations-for-using-the-data)
-  - [Social Impact of Dataset](#social-impact-of-dataset)
-  - [Discussion of Biases](#discussion-of-biases)
-  - [Other Known Limitations](#other-known-limitations)
-- [Additional Information](#additional-information)
-  - [Dataset Curators](#dataset-curators)
-  - [Licensing Information](#licensing-information)
-  - [Citation Information](#citation-information)
-  - [Contributions](#contributions)
-
-## Dataset Description
-
-- **Homepage:** [https://www.hlt.utdallas.edu/~vince/data/emnlp12/](https://www.hlt.utdallas.edu/~vince/data/emnlp12/)
-- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-- **Size of downloaded dataset files:** 0.23 MB
-- **Size of the generated dataset:** 0.24 MB
-- **Total amount of disk used:** 0.47 MB
-
-### Dataset Summary
-
-Composed by 30 students from one of the author's undergraduate classes. These
-sentence pairs cover topics ranging from real events (e.g., Iran's plan to
-attack the Saudi ambassador to the U.S.) to events/characters in movies (e.g.,
-Batman) and purely imaginary situations, largely reflecting the pop culture as
-perceived by the American kids born in the early 90s. Each annotated example
-spans four lines: the first line contains the sentence, the second line contains
-the target pronoun, the third line contains the two candidate antecedents, and
-the fourth line contains the correct antecedent. If the target pronoun appears
-more than once in the sentence, its first occurrence is the one to be resolved.
-
-### Supported Tasks and Leaderboards
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Languages
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-## Dataset Structure
-
-### Data Instances
-
-#### plain_text
-
-- **Size of downloaded dataset files:** 0.23 MB
-- **Size of the generated dataset:** 0.24 MB
-- **Total amount of disk used:** 0.47 MB
-
-An example of 'train' looks as follows.
-```
-{
-    "candidates": ["coreference resolution", "chunking"],
-    "label": 0,
-    "pronoun": "it",
-    "sentence": "There is currently more work on coreference resolution than on chunking because it is a problem that is still far from being solved."
-}
-```
-
-### Data Fields
-
-The data fields are the same among all splits.
-
-#### plain_text
-- `sentence`: a `string` feature.
-- `pronoun`: a `string` feature.
-- `candidates`: a `list` of `string` features.
-- `label`: a classification label, with possible values including `0` (0), `1` (1).
-
-### Data Splits
-
-|   name   |train|test|
-|----------|----:|---:|
-|plain_text| 1322| 564|
-
-## Dataset Creation
-
-### Curation Rationale
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Source Data
-
-#### Initial Data Collection and Normalization
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-#### Who are the source language producers?
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Annotations
-
-#### Annotation process
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-#### Who are the annotators?
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Personal and Sensitive Information
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-## Considerations for Using the Data
-
-### Social Impact of Dataset
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Discussion of Biases
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Other Known Limitations
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-## Additional Information
-
-### Dataset Curators
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Licensing Information
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Citation Information
-
-```
-@inproceedings{rahman2012resolving,
-  title={Resolving complex cases of definite pronouns: the winograd schema challenge},
-  author={Rahman, Altaf and Ng, Vincent},
-  booktitle={Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning},
-  pages={777--789},
-  year={2012},
-  organization={Association for Computational Linguistics}
-}
-```
-
-
-### Contributions
-
-Thanks to [@thomwolf](https://github.com/thomwolf), [@lewtun](https://github.com/lewtun), [@patrickvonplaten](https://github.com/patrickvonplaten) for adding this dataset.

dataset_infos.json

@@ -1 +0,0 @@
-{"plain_text": {"description": "Composed by 30 students from one of the author's undergraduate classes. These\nsentence pairs cover topics ranging from real events (e.g., Iran's plan to\nattack the Saudi ambassador to the U.S.) to events/characters in movies (e.g.,\nBatman) and purely imaginary situations, largely reflecting the pop culture as\nperceived by the American kids born in the early 90s. Each annotated example\nspans four lines: the first line contains the sentence, the second line contains\nthe target pronoun, the third line contains the two candidate antecedents, and\nthe fourth line contains the correct antecedent. If the target pronoun appears\nmore than once in the sentence, its first occurrence is the one to be resolved.\n", "citation": "@inproceedings{rahman2012resolving,\n  title={Resolving complex cases of definite pronouns: the winograd schema challenge},\n  author={Rahman, Altaf and Ng, Vincent},\n  booktitle={Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning},\n  pages={777--789},\n  year={2012},\n  organization={Association for Computational Linguistics}\n}", "homepage": "http://www.hlt.utdallas.edu/~vince/data/emnlp12/", "license": "", "features": {"sentence": {"dtype": "string", "id": null, "_type": "Value"}, "pronoun": {"dtype": "string", "id": null, "_type": "Value"}, "candidates": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": 2, "id": null, "_type": "Sequence"}, "label": {"num_classes": 2, "names": ["0", "1"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": {"input": "sentence", "output": "label"}, "task_templates": null, "builder_name": "definite_pronoun_resolution", "config_name": "plain_text", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 71691, "num_examples": 564, "dataset_name": "definite_pronoun_resolution"}, "train": {"name": "train", "num_bytes": 171511, "num_examples": 1322, "dataset_name": "definite_pronoun_resolution"}}, "download_checksums": {"https://s3.amazonaws.com/datasets.huggingface.co/definite_pronoun_resolution/train.c.txt": {"num_bytes": 160408, "checksum": "c310158d0cbac1a556e3284e6c167f4478271d8d50b0b9d15dfe428c905a0867"}, "https://s3.amazonaws.com/datasets.huggingface.co/definite_pronoun_resolution/test.c.txt": {"num_bytes": 67044, "checksum": "cf1cf025e1d59a5b363e6dcfbd5a13aae8a9830831ac16fd7f865aca7a1559d8"}}, "download_size": 227452, "post_processing_size": null, "dataset_size": 243202, "size_in_bytes": 470654}}

definite_pronoun_resolution.py

@@ -1,105 +0,0 @@
-# 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
-"""The Definite Pronoun Resolution Dataset."""
-
-
-import datasets
-
-
-_CITATION = """\
-@inproceedings{rahman2012resolving,
-  title={Resolving complex cases of definite pronouns: the winograd schema challenge},
-  author={Rahman, Altaf and Ng, Vincent},
-  booktitle={Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning},
-  pages={777--789},
-  year={2012},
-  organization={Association for Computational Linguistics}
-}"""
-
-_DESCRIPTION = """\
-Composed by 30 students from one of the author's undergraduate classes. These
-sentence pairs cover topics ranging from real events (e.g., Iran's plan to
-attack the Saudi ambassador to the U.S.) to events/characters in movies (e.g.,
-Batman) and purely imaginary situations, largely reflecting the pop culture as
-perceived by the American kids born in the early 90s. Each annotated example
-spans four lines: the first line contains the sentence, the second line contains
-the target pronoun, the third line contains the two candidate antecedents, and
-the fourth line contains the correct antecedent. If the target pronoun appears
-more than once in the sentence, its first occurrence is the one to be resolved.
-"""
-
-
-_DATA_URL_PATTERN = "https://s3.amazonaws.com/datasets.huggingface.co/definite_pronoun_resolution/{}.c.txt"
-
-
-class DefinitePronounResolution(datasets.GeneratorBasedBuilder):
-    """The Definite Pronoun Resolution Dataset."""
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(
-            name="plain_text",
-            version=datasets.Version("1.0.0", ""),
-            description="Plain text import of the Definite Pronoun Resolution Dataset.",  # pylint: disable=line-too-long
-        )
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "sentence": datasets.Value("string"),
-                    "pronoun": datasets.Value("string"),
-                    "candidates": datasets.features.Sequence(datasets.Value("string"), length=2),
-                    "label": datasets.features.ClassLabel(num_classes=2),
-                }
-            ),
-            supervised_keys=("sentence", "label"),
-            homepage="http://www.hlt.utdallas.edu/~vince/data/emnlp12/",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        files = dl_manager.download_and_extract(
-            {
-                "train": _DATA_URL_PATTERN.format("train"),
-                "test": _DATA_URL_PATTERN.format("test"),
-            }
-        )
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": files["test"]}),
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": files["train"]}),
-        ]
-
-    def _generate_examples(self, filepath):
-        with open(filepath, encoding="utf-8") as f:
-            line_num = -1
-            while True:
-                line_num += 1
-                sentence = f.readline().strip()
-                pronoun = f.readline().strip()
-                candidates = [c.strip() for c in f.readline().strip().split(",")]
-                correct = f.readline().strip()
-                f.readline()
-                if not sentence:
-                    break
-                yield line_num, {
-                    "sentence": sentence,
-                    "pronoun": pronoun,
-                    "candidates": candidates,
-                    "label": candidates.index(correct),
-                }

plain_text/test/0000.parquet

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+size 32221

plain_text/train/0000.parquet

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