annotations_creators:
- found
language_creators:
- found
languages:
- zh
licenses:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- extractive-qa
Dataset Card for LiveQA
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: Github
- Repository: Github
- Paper: Liu et al., 2020
- Leaderboard: N/A
- Point of Contact: Qianying Liu
Dataset Summary
The LiveQA dataset is a Chinese question-answering resource constructed from playby-play live broadcasts. It contains 117k multiple-choice questions written by human commentators for over 1,670 NBA games, which are collected from the Chinese Hupu website.
Supported Tasks and Leaderboards
Question Answering.
[More Information Needed]
Languages
Chinese.
Dataset Structure
Data Instances
Each instance represents a timeline (i.e., a game) with an identifier. The passages field comprise an array of text or question segments. In the following truncated example, user comments about the game is followed by a question about which team will be the first to reach 60 points.
{
'id': 1,
'passages': [
{
"is_question": False,
"text": "'我希望两位球员都能做到！！",
"candidate1": "",
"candidate2": "",
"answer": "",
},
{
"is_question": False,
"text": "新年给我们送上精彩比赛！",
"candidate1": "",
"candidate2": "",
"answer": "",
},
{
"is_question": True,
"text": "先达到60分？",
"candidate1": "火箭",
"candidate2": "勇士",
"answer": "勇士",
},
{
"is_question": False,
"text": "自己急停跳投！！！",
"candidate1": "",
"candidate2": "",
"answer": "",
}
]
}
Data Fields
- id: identifier for the game
- passages: collection of text/question segments
- text: real-time text comment or binary question related to the context
- candidate1/2: one of the two answer options to the question
- answer: correct answer to the question in text
Data Splits
There is no predefined split in this dataset.
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
[More Information Needed]
Citation Information
This resource is developed by Liu et al., 2020.
@inproceedings{qianying-etal-2020-liveqa,
title = "{L}ive{QA}: A Question Answering Dataset over Sports Live",
author = "Qianying, Liu and
Sicong, Jiang and
Yizhong, Wang and
Sujian, Li",
booktitle = "Proceedings of the 19th Chinese National Conference on Computational Linguistics",
month = oct,
year = "2020",
address = "Haikou, China",
publisher = "Chinese Information Processing Society of China",
url = "https://www.aclweb.org/anthology/2020.ccl-1.98",
pages = "1057--1067"
}