
# Dataset Card for LSOIE

## 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:** https://github.com/Jacobsolawetz/large-scale-oie
- **Repository:** https://github.com/Jacobsolawetz/large-scale-oie
- **Paper:** https://arxiv.org/abs/2101.11177
- **Leaderboard:** [Needs More Information]
- **Point of Contact:** [Needs More Information]

### Dataset Summary

The Large Scale Open Information Extraction Dataset (LSOIE), is a dataset 20 times larger than the next largest human-annotated Open Information Extraction (OIE) dataset. LSOIE is a built upon the QA-SRL 2.0 dataset by transforming the list of Questions and answers for each predicate to a tuple representing a fact.

### Supported Tasks and Leaderboards

Open Information Extraction

### Languages

The text in this dataset is english.

## Dataset Structure

### Data Instances

A datapoint comprises one fact together with the sentence it was extracted from. There can be multiple facts for each Sentence. Each fact is represented by a tuple $(a_0, p, a_1,\dots a_n)$ where $a_0$ is the head entity $p$ is the predicate and $a_1, \dots,a_n$ represent the tail.

### Data Fields

- word_ids : sequence of indices (int) representing tokens in a sentence,
- words : a sequence of strings, the tokens in the sentence,
- pred : the predicate of the fact,
- pred_ids : ids of the tokens in the predicate,
- head_pred_id : id of the head token in the predicate,
- sent_id : sentence id,
- run_id : ,
- label : Sequence of tags (BIO) representing the fact, e.g. if the fact is given by $(a_0, p, a_1, \dots, a_n) $

### Data Splits

[Needs More Information]

## 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

[Needs More Information]

### Licensing Information

[Needs More Information]

### Citation Information

[Needs More Information]
task_categories:text-retrieval annotations_creators:machine-generated language_creators:found multilinguality:monolingual size_categories:unknown source_datasets:extended|qa_srl language:en license:mit Open Information Extraction arxiv:2101.11177 region:us
{"annotations_creators": ["machine-generated"], "language_creators": ["found"], "language": ["en"], "license": ["mit"], "multilinguality": ["monolingual"], "size_categories": ["unknown"], "source_datasets": ["extended|qa_srl"], "task_categories": ["text-retrieval"], "task_ids": [], "pretty_name": "LSOIE", "tags": ["Open Information Extraction"]}
TAGS
#task_categories-text-retrieval #annotations_creators-machine-generated #language_creators-found #multilinguality-monolingual #size_categories-unknown #source_datasets-extended|qa_srl #language-English #license-mit #Open Information Extraction #arxiv-2101.11177 #region-us 


# Dataset Card for LSOIE

## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information

## Dataset Description

- Homepage: URL
- Repository: URL
- Paper: URL
- Leaderboard: 
- Point of Contact: 

### Dataset Summary

The Large Scale Open Information Extraction Dataset (LSOIE), is a dataset 20 times larger than the next largest human-annotated Open Information Extraction (OIE) dataset. LSOIE is a built upon the QA-SRL 2.0 dataset by transforming the list of Questions and answers for each predicate to a tuple representing a fact.

### Supported Tasks and Leaderboards

Open Information Extraction

### Languages

The text in this dataset is english.

## Dataset Structure

### Data Instances

A datapoint comprises one fact together with the sentence it was extracted from. There can be multiple facts for each Sentence. Each fact is represented by a tuple $(a_0, p, a_1,\dots a_n)$ where $a_0$ is the head entity $p$ is the predicate and $a_1, \dots,a_n$ represent the tail.

### Data Fields

- word_ids : sequence of indices (int) representing tokens in a sentence,
- words : a sequence of strings, the tokens in the sentence,
- pred : the predicate of the fact,
- pred_ids : ids of the tokens in the predicate,
- head_pred_id : id of the head token in the predicate,
- sent_id : sentence id,
- run_id : ,
- label : Sequence of tags (BIO) representing the fact, e.g. if the fact is given by $(a_0, p, a_1, \dots, a_n) $

### Data Splits



## Dataset Creation

### Curation Rationale



### Source Data

#### Initial Data Collection and Normalization



#### Who are the source language producers?



### Annotations

#### Annotation process



#### Who are the annotators?



### Personal and Sensitive Information



## Considerations for Using the Data

### Social Impact of Dataset



### Discussion of Biases



### Other Known Limitations



## Additional Information

### Dataset Curators



### Licensing Information






# Dataset Card for LSOIE ## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information ## Dataset Description

- Homepage: URL
- Repository: URL
- Paper: URL
- Leaderboard: 
- Point of Contact: ### Dataset Summary

The Large Scale Open Information Extraction Dataset (LSOIE), is a dataset 20 times larger than the next largest human-annotated Open Information Extraction (OIE) dataset. LSOIE is a built upon the QA-SRL 2.0 dataset by transforming the list of Questions and answers for each predicate to a tuple representing a fact. ### Supported Tasks and Leaderboards

Open Information Extraction ### Languages

The text in this dataset is english. ## Dataset Structure ### Data Instances

A datapoint comprises one fact together with the sentence it was extracted from. There can be multiple facts for each Sentence. Each fact is represented by a tuple $(a_0, p, a_1,\dots a_n)$ where $a_0$ is the head entity $p$ is the predicate and $a_1, \dots,a_n$ represent the tail. ### Data Fields

- word_ids : sequence of indices (int) representing tokens in a sentence,
- words : a sequence of strings, the tokens in the sentence,
- pred : the predicate of the fact,
- pred_ids : ids of the tokens in the predicate,
- head_pred_id : id of the head token in the predicate,
- sent_id : sentence id,
- run_id : ,
- label : Sequence of tags (BIO) representing the fact, e.g. if the fact is given by $(a_0, p, a_1, \dots, a_n) $ ### Data Splits ## Dataset Creation ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations ## Additional Information ### Dataset Curators ### Licensing Information
TAGS
#task_categories-text-retrieval #annotations_creators-machine-generated #language_creators-found #multilinguality-monolingual #size_categories-unknown #source_datasets-extended|qa_srl #language-English #license-mit #Open Information Extraction #arxiv-2101.11177 #region-us 
 # Dataset Card for LSOIE ## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information ## Dataset Description

- Homepage: URL
- Repository: URL
- Paper: URL
- Leaderboard: 
- Point of Contact: ### Dataset Summary

The Large Scale Open Information Extraction Dataset (LSOIE), is a dataset 20 times larger than the next largest human-annotated Open Information Extraction (OIE) dataset. LSOIE is a built upon the QA-SRL 2.0 dataset by transforming the list of Questions and answers for each predicate to a tuple representing a fact. ### Supported Tasks and Leaderboards

Open Information Extraction ### Languages

The text in this dataset is english. ## Dataset Structure ### Data Instances

A datapoint comprises one fact together with the sentence it was extracted from. There can be multiple facts for each Sentence. Each fact is represented by a tuple $(a_0, p, a_1,\dots a_n)$ where $a_0$ is the head entity $p$ is the predicate and $a_1, \dots,a_n$ represent the tail. ### Data Fields

- word_ids : sequence of indices (int) representing tokens in a sentence,
- words : a sequence of strings, the tokens in the sentence,
- pred : the predicate of the fact,
- pred_ids : ids of the tokens in the predicate,
- head_pred_id : id of the head token in the predicate,
- sent_id : sentence id,
- run_id : ,
- label : Sequence of tags (BIO) representing the fact, e.g. if the fact is given by $(a_0, p, a_1, \dots, a_n) $ ### Data Splits ## Dataset Creation ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations ## Additional Information ### Dataset Curators ### Licensing Information