Datasets:
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---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- multiple-choice-qa
- open-domain-qa
paperswithcode_id: qa-srl
pretty_name: QA-SRL
dataset_info:
features:
- name: sentence
dtype: string
- name: sent_id
dtype: string
- name: predicate_idx
dtype: int32
- name: predicate
dtype: string
- name: question
sequence: string
- name: answers
sequence: string
config_name: plain_text
splits:
- name: train
num_bytes: 1835549
num_examples: 6414
- name: validation
num_bytes: 632992
num_examples: 2183
- name: test
num_bytes: 637317
num_examples: 2201
download_size: 1087729
dataset_size: 3105858
---
# Dataset Card for QA-SRL
## 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:** [Homepage](https://dada.cs.washington.edu/qasrl/#page-top)
- **Annotation Tool:** [Annotation tool](https://github.com/luheng/qasrl_annotation)
- **Repository:** [Repository](https://dada.cs.washington.edu/qasrl/#dataset)
- **Paper:** [Qa_srl paper](https://www.aclweb.org/anthology/D15-1076.pdf)
- **Point of Contact:** [Luheng He](luheng@cs.washington.edu)
### Dataset Summary
we model predicate-argument structure of a sentence with a set of question-answer pairs. our method allows practical large-scale annotation of training data. We focus on semantic rather than syntactic annotation, and introduce a scalable method for gathering data that allows both training and evaluation.
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
This dataset is in english language.
## Dataset Structure
### Data Instances
We use question-answer pairs to model verbal predicate-argument structure. The questions start with wh-words (Who, What, Where, What, etc.) and contains a verb predicate in the sentence; the answers are phrases in the sentence. For example:
`UCD finished the 2006 championship as Dublin champions , by beating St Vincents in the final .`
Predicate | Question | Answer
---|---|---|
|Finished|Who finished something? | UCD
|Finished|What did someone finish?|the 2006 championship
|Finished|What did someone finish something as? |Dublin champions
|Finished|How did someone finish something? |by beating St Vincents in the final
|beating | Who beat someone? | UCD
|beating|When did someone beat someone? |in the final
|beating|Who did someone beat?| St Vincents
### Data Fields
Annotations provided are as follows:
- `sentence`: contains tokenized sentence
- `sent_id`: is the sentence identifier
- `predicate_idx`:the index of the predicate (its position in the sentence)
- `predicate`: the predicate token
- `question`: contains the question which is a list of tokens. The question always consists of seven slots, as defined in the paper. The empty slots are represented with a marker “_”. The question ends with question mark.
- `answer`: list of answers to the question
### Data Splits
Dataset | Sentences | Verbs | QAs
--- | --- | --- |---|
**newswire-train**|744|2020|4904|
**newswire-dev**|249|664|1606|
**newswire-test**|248|652|1599
**Wikipedia-train**|`1174`|`2647`|`6414`|
**Wikipedia-dev**|`392`|`895`|`2183`|
**Wikipedia-test**|`393`|`898`|`2201`|
**Please note**
This dataset only has wikipedia data. Newswire dataset needs CoNLL-2009 English training data to get the complete data. This training data is under license. Thus, newswire dataset is not included in this data.
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
We annotated over 3000 sentences (nearly 8,000 verbs) in total across two domains: newswire (PropBank) and Wikipedia.
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
non-expert annotators were given a short tutorial and a small set of sample annotations (about 10 sentences). Annotators were hired if they showed good understanding of English and the task. The entire screening process usually took less than 2 hours.
#### Who are the annotators?
10 part-time, non-exper annotators from Upwork (Previously oDesk)
### 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
[Luheng He](luheng@cs.washington.edu)
### Licensing Information
[More Information Needed]
### Citation Information
```
@InProceedings{huggingface:dataset,
title = {QA-SRL: Question-Answer Driven Semantic Role Labeling},
authors={Luheng He, Mike Lewis, Luke Zettlemoyer},
year={2015}
publisher = {cs.washington.edu},
howpublished={\\url{https://dada.cs.washington.edu/qasrl/#page-top}},
}
```
### Contributions
Thanks to [@bpatidar](https://github.com/bpatidar) for adding this dataset. |