allenai/tuple_ie

---
annotations_creators:
- found
language_creators:
- machine-generated
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- other
task_ids: []
paperswithcode_id: tupleinf-open-ie-dataset
pretty_name: TupleInf Open IE
tags:
- open-information-extraction
dataset_info:
- config_name: all
features:
- name: sentence
dtype: string
- name: tuples
sequence:
- name: score
dtype: float32
- name: tuple_text
dtype: string
- name: context
dtype: string
- name: arg1
dtype: string
- name: rel
dtype: string
- name: arg2s
sequence: string
splits:
- name: train
num_bytes: 115621096
num_examples: 267719
download_size: 18026102
dataset_size: 115621096
- config_name: 4th_grade
features:
- name: sentence
dtype: string
- name: tuples
sequence:
- name: score
dtype: float32
- name: tuple_text
dtype: string
- name: context
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num_examples: 158910
download_size: 18026102
dataset_size: 65363445
- config_name: 8th_grade
features:
- name: sentence
dtype: string
- name: tuples
sequence:
- name: score
dtype: float32
- name: tuple_text
dtype: string
- name: context
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- name: arg1
dtype: string
- name: rel
dtype: string
- name: arg2s
sequence: string
splits:
- name: train
num_bytes: 50257651
num_examples: 108809
download_size: 18026102
dataset_size: 50257651
---

# Dataset Card for TupleInf Open IE

## 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:** [Tuple IE Homepage](https://allenai.org/data/tuple-ie)
- **Repository:**
- **Paper:** [Answering Complex Questions Using Open Information Extraction](https://www.semanticscholar.org/paper/Answering-Complex-Questions-Using-Open-Information-Khot-Sabharwal/0ff595f0645a3e25a2f37145768985b10ead0509)
- **Leaderboard:**
- **Point of Contact:**

### Dataset Summary

The TupleInf Open IE dataset contains Open IE tuples extracted from 263K sentences that were used by the solver in “Answering Complex Questions Using Open Information Extraction” (referred as Tuple KB, T). These sentences were collected from a large Web corpus using training questions from 4th and 8th grade as queries. This dataset contains 156K sentences collected for 4th grade questions and 107K sentences for 8th grade questions. Each sentence is followed by the Open IE v4 tuples using their simple format.

### Supported Tasks and Leaderboards

[More Information Needed]

### Languages

The text in the dataset is in English, collected from a large Web corpus using training questions from 4th and 8th grade as queries.

## Dataset Structure

### Data Instances

This dataset contains setences with corresponding relation tuples extracted from each sentence. Each instance should contain a sentence and followed by the [Open IE v4](https://github.com/allenai/openie-standalone) tuples using their *simple format*.
An example of an instance:

```JSON
{
"sentence": "0.04593 kg Used a triple beam balance to mass a golf ball.",
"tuples": {
"score": 0.8999999761581421,
"tuple_text": "(0.04593 kg; Used; a triple beam balance; to mass a golf ball)",
"context": "",
"arg1": "0.04593 kg",
"rel": "Used",
"arg2s": ["a triple beam balance", "to mass a golf ball"],
}
}
```

### Data Fields

- `sentence`: the input text/sentence.
- `tuples`: the extracted relation tuples from the sentence.
- `score`: the confident score for each tuple.
- `tuple_text`: the relationship representation text of the extraction, in the *simple format* of [Open IE v4](https://github.com/allenai/openie-standalone).
- `context`: an optional representation of the context for this extraction. Defaults to `""` if there's no context.
- `arg1`: the first argument in the relationship.
- `rel`: the relation.
- `arg2s`: a sequence of the 2nd arguments in the realtionship.

### Data Splits

| name | train|
|-----------|-----:|
| all |267719|
| 4th_grade |158910|
| 8th_grade |108809|

## 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

```bibtex
@article{Khot2017AnsweringCQ,
title={Answering Complex Questions Using Open Information Extraction},
author={Tushar Khot and A. Sabharwal and Peter Clark},
journal={ArXiv},
year={2017},
volume={abs/1704.05572}
}
```

### Contributions

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

原始信息汇总

数据集概述

数据集基本信息

• 名称: TupleInf Open IE
• 语言: 英语
• 许可: 未知
• 多语言性: 单语种
• 大小类别: 100K<n<1M
• 源数据集: 原始数据
• 任务类别: 其他
• 标签: open-information-extraction

数据集结构

数据实例

每个实例包含一个句子及其对应的Open IE v4关系元组。

数据字段

• sentence: 输入文本/句子。
• tuples: 从句子中提取的关系元组。
  • score: 每个元组的置信度分数。
  • tuple_text: 提取的关系表示文本，采用Open IE v4的简单格式。
  • context: 此提取的可选上下文表示。如果没有上下文，则默认为空字符串。
  • arg1: 关系中的第一个参数。
  • rel: 关系。
  • arg2s: 关系中的第二个参数序列。

数据分割

名称	训练集数量
all	267719
4th_grade	158910
8th_grade	108809

数据集创建

数据集摘要

TupleInf Open IE数据集包含从263K个句子中提取的Open IE元组，这些句子用于“使用开放信息提取回答复杂问题”（称为Tuple KB，T）中的求解器。这些句子是从使用4年级和8年级训练问题作为查询的大型网络语料库中收集的。该数据集包含为4年级问题收集的156K个句子和为8年级问题收集的107K个句子。每个句子后面都跟着使用其简单格式的Open IE v4元组。

搜集汇总

背景与挑战

背景概述

该数据集是一个开放信息抽取（Open IE）数据集，包含从26.3万英语句子中提取的元组，这些句子源自网络语料库，并使用4年级和8年级训练问题作为查询收集。数据集主要用于支持复杂问答任务，每个实例包括句子和对应的Open IE v4简单格式元组，涵盖参数、关系和置信度分数等字段。