Serverless/dev_mode-wtq

---
annotations_creators:
- crowdsourced
language_creators:
- found
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
paperswithcode_id: null
pretty_name: WikiTableQuestions-wtq
size_categories:
- 10K<n<100K
source_datasets:
- wikitablequestions
task_categories:
- question-answering
task_ids: []
tags:
- table-question-answering
---

# Dataset Card for dev_mode-wtq

## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-instances)
- [Data Splits](#data-instances)
- [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)

## Dataset Description

- **Homepage:** [WikiTableQuestions homepage](https://nlp.stanford.edu/software/sempre/wikitable)
- **Repository:** [WikiTableQuestions repository](https://github.com/ppasupat/WikiTableQuestions)
- **Paper:** [Compositional Semantic Parsing on Semi-Structured Tables](https://arxiv.org/abs/1508.00305)
- **Leaderboard:** [WikiTableQuestions leaderboard on PaperWithCode](https://paperswithcode.com/dataset/wikitablequestions)
- **Point of Contact:** [Needs More Information]

### Dataset Summary

The dev_mode-wtq dataset is a small-scale dataset for the task of question answering on semi-structured tables.

This data includes the `aggregation_label` and `answer_coordinates` to make it easy to train this model on any [TAPAS](https://huggingface.co/docs/transformers/model_doc/tapas#usage-finetuning) based modles.

### Supported Tasks and Leaderboards

question-answering, table-question-answering

### Languages

en

## Dataset Structure

### Data Instances

#### default

- **Size of downloaded dataset files:** 27.91 MB
- **Size of the generated dataset:** 45.68 MB
- **Total amount of disk used:** 73.60 MB

An example of 'validation' looks as follows:
```
{
"id": "nt-0",
"question": "What is the duration for the last invocation?",
"answers": [
"340 ms"
],
"table": {
"header": [
"recent",
"type",
"spans",
"logs",
"errors",
"warnings",
"duration",
"resource"
],
"rows": [
[
"1",
"span",
"1",
"1",
"1",
"2",
"340 ms",
"aws-lambda-typescript-express-dev-express"
]
]
}
}
```

### Data Fields

The data fields are the same among all splits.

#### default
- `id`: a `string` feature.
- `question`: a `string` feature.
- `answers`: a `list` of `string` feature.
- `answers_coordinates`: a `list` of `int,int` tuples.
- `aggregation_label`: a `string` feature.
- `table`: a dictionary feature containing:
- `header`: a `list` of `string` features.
- `rows`: a `list` of `list` of `string` features:
- `name`: a `string` feature.

### Data Splits

TBA

## Dataset Creation

### Curation Rationale

[Needs More Information]

### Source Data

#### Initial Data Collection and Normalization

[Needs More Information]

#### Who are the source language producers?

[Needs More Information]

### Annotations

#### Annotation process

[Needs More Information]

#### Who are the annotators?

[Needs More Information]

### Personal and Sensitive Information

[Needs More Information]

## Considerations for Using the Data

### Social Impact of Dataset

[Needs More Information]

### Discussion of Biases

[Needs More Information]

### Other Known Limitations

[Needs More Information]

## Additional Information

### Dataset Curators

Panupong Pasupat and Percy Liang

### Licensing Information

Creative Commons Attribution Share Alike 4.0 International

### Citation Information

```
@inproceedings{pasupat-liang-2015-compositional,
title = "Compositional Semantic Parsing on Semi-Structured Tables",
author = "Pasupat, Panupong and Liang, Percy",
booktitle = "Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)",
month = jul,
year = "2015",
address = "Beijing, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P15-1142",
doi = "10.3115/v1/P15-1142",
pages = "1470--1480",
}
```

### Contributions

Thanks to [@SivilTaram](https://github.com/SivilTaram) for adding this dataset.

原始信息汇总

数据集概述

数据集名称

• 名称: dev_mode-wtq
• 别名: WikiTableQuestions-wtq

数据集基本信息

• 语言: 英语 (en)
• 许可证: Creative Commons Attribution Share Alike 4.0 International (cc-by-4.0)
• 多语言性: 单语
• 大小: 10K<n<100K

数据集创建

• 注释创建者: 众包
• 语言创建者: 发现
• 数据集来源: wikitablequestions

任务与应用

• 任务类别: 问答 (question-answering), 表格问答 (table-question-answering)

数据集结构

• 数据实例:

  • 下载大小: 27.91 MB
  • 生成数据集大小: 45.68 MB
  • 总磁盘使用: 73.60 MB
  • 示例: json { "id": "nt-0", "question": "What is the duration for the last invocation?", "answers": ["340 ms"], "table": { "header": ["recent", "type", "spans", "logs", "errors", "warnings", "duration", "resource"], "rows": [["1", "span", "1", "1", "1", "2", "340 ms", "aws-lambda-typescript-express-dev-express"]] } }

• 数据字段:

  • id: 字符串
  • question: 字符串
  • answers: 字符串列表
  • answers_coordinates: 整数元组列表
  • aggregation_label: 字符串
  • table: 字典，包含表头和行数据

数据集创建者

• 数据集创建者: Panupong Pasupat 和 Percy Liang

许可证信息

• 许可证: Creative Commons Attribution Share Alike 4.0 International

引用信息

@inproceedings{pasupat-liang-2015-compositional, title = "Compositional Semantic Parsing on Semi-Structured Tables", author = "Pasupat, Panupong and Liang, Percy", booktitle = "Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)", month = jul, year = "2015", address = "Beijing, China", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/P15-1142", doi = "10.3115/v1/P15-1142", pages = "1470--1480", }