Datasets:

Modalities:
Text
Formats:
parquet
Sub-tasks:
extractive-qa
Languages:
English
ArXiv:
Libraries:
Datasets
pandas
License:
system HF staff commited on
Commit
5103141
1 Parent(s): 8411283

Update files from the datasets library (from 1.7.0)

Browse files

Release notes: https://github.com/huggingface/datasets/releases/tag/1.7.0

Files changed (1) hide show
  1. README.md +17 -4
README.md CHANGED
@@ -18,6 +18,7 @@ task_categories:
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  - question-answering
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  task_ids:
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  - extractive-qa
 
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  ---
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  # Dataset Card for "squad"
@@ -25,12 +26,12 @@ task_ids:
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  ## Table of Contents
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  - [Dataset Description](#dataset-description)
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  - [Dataset Summary](#dataset-summary)
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- - [Supported Tasks](#supported-tasks)
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  - [Languages](#languages)
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  - [Dataset Structure](#dataset-structure)
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  - [Data Instances](#data-instances)
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  - [Data Fields](#data-fields)
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- - [Data Splits Sample Size](#data-splits-sample-size)
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  - [Dataset Creation](#dataset-creation)
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  - [Curation Rationale](#curation-rationale)
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  - [Source Data](#source-data)
@@ -60,7 +61,7 @@ task_ids:
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  Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage, or the question might be unanswerable.
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- ### Supported Tasks
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  [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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@@ -107,7 +108,7 @@ The data fields are the same among all splits.
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  - `text`: a `string` feature.
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  - `answer_start`: a `int32` feature.
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- ### Data Splits Sample Size
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  | name |train|validation|
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  |----------|----:|---------:|
@@ -121,10 +122,22 @@ The data fields are the same among all splits.
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  ### Source Data
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  [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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  ### Annotations
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  [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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  ### Personal and Sensitive Information
 
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  - question-answering
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  task_ids:
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  - extractive-qa
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+ paperswithcode_id: squad
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  ---
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  # Dataset Card for "squad"
 
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  ## Table of Contents
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  - [Dataset Description](#dataset-description)
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  - [Dataset Summary](#dataset-summary)
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+ - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
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  - [Languages](#languages)
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  - [Dataset Structure](#dataset-structure)
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  - [Data Instances](#data-instances)
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  - [Data Fields](#data-fields)
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+ - [Data Splits](#data-splits)
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  - [Dataset Creation](#dataset-creation)
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  - [Curation Rationale](#curation-rationale)
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  - [Source Data](#source-data)
 
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  Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage, or the question might be unanswerable.
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+ ### Supported Tasks and Leaderboards
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  [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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  - `text`: a `string` feature.
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  - `answer_start`: a `int32` feature.
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+ ### Data Splits
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  | name |train|validation|
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  |----------|----:|---------:|
 
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  ### Source Data
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+ #### Initial Data Collection and Normalization
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+
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+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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+
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+ #### Who are the source language producers?
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+
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  [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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  ### Annotations
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+ #### Annotation process
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+
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+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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+
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+ #### Who are the annotators?
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+
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  [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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  ### Personal and Sensitive Information