Languages: English
Multilinguality: monolingual
Size Categories: 10K<n<100K
Language Creators: found
Annotations Creators: crowdsourced
Source Datasets: original
eraser_multi_rc /
albertvillanova's picture
Convert dataset sizes from base 2 to base 10 in the dataset card (#2)
- crowdsourced
- found
- en
- other
- monolingual
- 10K<n<100K
- original
- multiple-choice
- multiple-choice-qa
pretty_name: Eraser MultiRC (Multi-Sentence Reading Comprehension)
- name: passage
dtype: string
- name: query_and_answer
dtype: string
- name: label
'0': 'False'
'1': 'True'
- name: evidences
sequence: string
- name: test
num_bytes: 9194475
num_examples: 4848
- name: train
num_bytes: 47922877
num_examples: 24029
- name: validation
num_bytes: 6529020
num_examples: 3214
download_size: 1667550
dataset_size: 63646372
# Dataset Card for "eraser_multi_rc"
## 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:**
- **Repository:**
- **Paper:** [Looking Beyond the Surface: A Challenge Set for Reading Comprehension over Multiple Sentences](
- **Point of Contact:** [More Information Needed](
- **Size of downloaded dataset files:** 1.67 MB
- **Size of the generated dataset:** 63.65 MB
- **Total amount of disk used:** 65.32 MB
### Dataset Summary
MultiRC (Multi-Sentence Reading Comprehension) is a dataset of short paragraphs and multi-sentence questions that can be answered from the content of the paragraph.
We have designed the dataset with three key challenges in mind:
- The number of correct answer-options for each question is not pre-specified. This removes the over-reliance of current approaches on answer-options and forces them to decide on the correctness of each candidate answer independently of others. In other words, unlike previous work, the task here is not to simply identify the best answer-option, but to evaluate the correctness of each answer-option individually.
- The correct answer(s) is not required to be a span in the text.
- The paragraphs in our dataset have diverse provenance by being extracted from 7 different domains such as news, fiction, historical text etc., and hence are expected to be more diverse in their contents as compared to single-domain datasets.
The goal of this dataset is to encourage the research community to explore approaches that can do more than sophisticated lexical-level matching.
### Supported Tasks and Leaderboards
[More Information Needed](
### Languages
[More Information Needed](
## Dataset Structure
### Data Instances
#### default
- **Size of downloaded dataset files:** 1.67 MB
- **Size of the generated dataset:** 63.65 MB
- **Total amount of disk used:** 65.32 MB
An example of 'validation' looks as follows.
This example was too long and was cropped:
"evidences": "[\"Allan sat down at his desk and pulled the chair in close .\", \"Opening a side drawer , he took out a piece of paper and his ink...",
"label": 0,
"passage": "\"Allan sat down at his desk and pulled the chair in close .\\nOpening a side drawer , he took out a piece of paper and his inkpot...",
"query_and_answer": "Name few objects said to be in or on Allan 's desk || Eraser"
### Data Fields
The data fields are the same among all splits.
#### default
- `passage`: a `string` feature.
- `query_and_answer`: a `string` feature.
- `label`: a classification label, with possible values including `False` (0), `True` (1).
- `evidences`: a `list` of `string` features.
### Data Splits
| name |train|validation|test|
|default|24029| 3214|4848|
## Dataset Creation
### Curation Rationale
[More Information Needed](
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed](
#### Who are the source language producers?
[More Information Needed](
### Annotations
#### Annotation process
[More Information Needed](
#### Who are the annotators?
[More Information Needed](
### Personal and Sensitive Information
[More Information Needed](
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed](
### Discussion of Biases
[More Information Needed](
### Other Known Limitations
[More Information Needed](
## Additional Information
### Dataset Curators
[More Information Needed](
### Licensing Information
Research and Academic Use License
Cognitive Computation Group
University of Illinois at Urbana-Champaign
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A. To use unlimited copies of the Software for its own academic and research purposes.
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### Citation Information
title = {ERASER: A Benchmark to Evaluate Rationalized NLP Models},
author = {Jay DeYoung and Sarthak Jain and Nazneen Fatema Rajani and Eric Lehman and Caiming Xiong and Richard Socher and Byron C. Wallace}
author = {Daniel Khashabi and Snigdha Chaturvedi and Michael Roth and Shyam Upadhyay and Dan Roth},
title = {Looking Beyond the Surface:A Challenge Set for Reading Comprehension over Multiple Sentences},
booktitle = {Proceedings of North American Chapter of the Association for Computational Linguistics (NAACL)},
year = {2018}
### Contributions
Thanks to [@lewtun](, [@patrickvonplaten](, [@thomwolf]( for adding this dataset.