

# Dataset Card for Quasimodo

## Table of Contents
- [Table of Contents](#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)
- [Dataset Creation](#dataset-creation)
- [Additional Information](#additional-information)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)


## Dataset Description

- **Homepage:** https://www.mpi-inf.mpg.de/departments/databases-and-information-systems/research/yago-naga/commonsense/quasimodo
- **Repository:** https://github.com/Aunsiels/CSK
- **Paper:** Romero et al., Commonsense Properties from Query Logs and Question Answering Forums, CIKM, 2019

### Dataset Summary

A commonsense knowledge base constructed automatically from question-answering forums and query logs.

### Supported Tasks and Leaderboards

Can be useful for tasks requiring external knowledge such as question answering.

### Languages

English

## Dataset Structure

### Data Instances

```python
{
  "subject": "elephant",
  "predicate": "has_body_part"
  "object": "trunk",
  "modality": "TBC[so long trunks] x#x2 // TBC[long trunks] x#x9 // TBC[big trunks] x#x6 // TBC[long trunk] x#x1 // TBC[such big trunks] x#x1	0	0.9999667967035647	elephants have trunks x#x34 x#xGoogle Autocomplete, Bing Autocomplete, Yahoo Questions, Answers.com Questions, Reddit Questions // a elephants have trunks x#x2 x#xGoogle Autocomplete // a elephant have a trunk x#x2 x#xGoogle Autocomplete // elephants have so long trunks x#x2 x#xGoogle Autocomplete // elephants have long trunks x#x8 x#xGoogle Autocomplete, Yahoo Questions, Answers.com Questions // elephants have big trunks x#x6 x#xGoogle Autocomplete, Answers.com Questions, Reddit Questions // elephants have trunk x#x3 x#xGoogle Autocomplete, Yahoo Questions // elephant have long trunks x#x1 x#xGoogle Autocomplete // elephant has a trunk x#x1 x#xGoogle Autocomplete // elephants have a trunk x#x2 x#xAnswers.com Questions // an elephant has a long trunk x#x1 x#xAnswers.com Questions // elephant have trunks x#x1 x#xAnswers.com Questions // elephants have such big trunks x#x1 x#xReddit Questions",
  "score": 0.9999667967668732,
  "local_sigma": 1.0
}
```

### Data Fields

- subject: The subject of the triple
- predicate: The predicate of the triple
- object: The object of the triple
- modality: Modalities associated with the triples with their counts. TBC means the object can be further refined to the listed objects
- is_negative: 1 if the statement was negated
- score: salience score of the supervised scoring model
- local sigma: strict conditional probability of observing a (predicate, object) with a specific subject. I.e., a measure of how unique a statement is. E.g., local_sigma(lawyers, defend, serial_killers) = 1, local_sigma(lawyers, make, money) = 0.01, even though both statements have a similar score of 0.99.



## Dataset Creation

See original paper.

## Additional Information

### Licensing Information

CC-BY 2.0

### Citation Information

Romero et al., Commonsense Properties from Query Logs and Question Answering Forums, CIKM, 2019

task_categories:question-answering task_ids:closed-domain-qa annotations_creators:machine-generated language_creators:machine-generated multilinguality:monolingual size_categories:100M<n<1B source_datasets:original language:en license:cc-by-2.0 knowledge base commonsense region:us
{"annotations_creators": ["machine-generated"], "language_creators": ["machine-generated"], "language": ["en"], "license": ["cc-by-2.0"], "multilinguality": ["monolingual"], "size_categories": ["100M<n<1B"], "source_datasets": ["original"], "task_categories": ["question-answering"], "task_ids": ["closed-domain-qa"], "pretty_name": "Quasimodo", "tags": ["knowledge base", "commonsense"]}
TAGS
#task_categories-question-answering #task_ids-closed-domain-qa #annotations_creators-machine-generated #language_creators-machine-generated #multilinguality-monolingual #size_categories-100M<n<1B #source_datasets-original #language-English #license-cc-by-2.0 #knowledge base #commonsense #region-us 



# Dataset Card for Quasimodo

## Table of Contents
- Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
- Dataset Creation
- Additional Information
  - Licensing Information
  - Citation Information


## Dataset Description

- Homepage: URL
- Repository: URL
- Paper: Romero et al., Commonsense Properties from Query Logs and Question Answering Forums, CIKM, 2019

### Dataset Summary

A commonsense knowledge base constructed automatically from question-answering forums and query logs.

### Supported Tasks and Leaderboards

Can be useful for tasks requiring external knowledge such as question answering.

### Languages

English

## Dataset Structure

### Data Instances



### Data Fields

- subject: The subject of the triple
- predicate: The predicate of the triple
- object: The object of the triple
- modality: Modalities associated with the triples with their counts. TBC means the object can be further refined to the listed objects
- is_negative: 1 if the statement was negated
- score: salience score of the supervised scoring model
- local sigma: strict conditional probability of observing a (predicate, object) with a specific subject. I.e., a measure of how unique a statement is. E.g., local_sigma(lawyers, defend, serial_killers) = 1, local_sigma(lawyers, make, money) = 0.01, even though both statements have a similar score of 0.99.



## Dataset Creation

See original paper.

## Additional Information

### Licensing Information

CC-BY 2.0



Romero et al., Commonsense Properties from Query Logs and Question Answering Forums, CIKM, 2019

# Dataset Card for Quasimodo ## Table of Contents
- Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
- Dataset Creation
- Additional Information
  - Licensing Information
  - Citation Information ## Dataset Description

- Homepage: URL
- Repository: URL
- Paper: Romero et al., Commonsense Properties from Query Logs and Question Answering Forums, CIKM, 2019 ### Dataset Summary

A commonsense knowledge base constructed automatically from question-answering forums and query logs. ### Supported Tasks and Leaderboards

Can be useful for tasks requiring external knowledge such as question answering. ### Languages

English ## Dataset Structure ### Data Instances ### Data Fields

- subject: The subject of the triple
- predicate: The predicate of the triple
- object: The object of the triple
- modality: Modalities associated with the triples with their counts. TBC means the object can be further refined to the listed objects
- is_negative: 1 if the statement was negated
- score: salience score of the supervised scoring model
- local sigma: strict conditional probability of observing a (predicate, object) with a specific subject. I.e., a measure of how unique a statement is. E.g., local_sigma(lawyers, defend, serial_killers) = 1, local_sigma(lawyers, make, money) = 0.01, even though both statements have a similar score of 0.99. ## Dataset Creation

See original paper. ## Additional Information ### Licensing Information

CC-BY 2.0



Romero et al., Commonsense Properties from Query Logs and Question Answering Forums, CIKM, 2019
TAGS
#task_categories-question-answering #task_ids-closed-domain-qa #annotations_creators-machine-generated #language_creators-machine-generated #multilinguality-monolingual #size_categories-100M<n<1B #source_datasets-original #language-English #license-cc-by-2.0 #knowledge base #commonsense #region-us 
 # Dataset Card for Quasimodo ## Table of Contents
- Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
- Dataset Creation
- Additional Information
  - Licensing Information
  - Citation Information ## Dataset Description

- Homepage: URL
- Repository: URL
- Paper: Romero et al., Commonsense Properties from Query Logs and Question Answering Forums, CIKM, 2019 ### Dataset Summary

A commonsense knowledge base constructed automatically from question-answering forums and query logs. ### Supported Tasks and Leaderboards

Can be useful for tasks requiring external knowledge such as question answering. ### Languages

English ## Dataset Structure ### Data Instances ### Data Fields

- subject: The subject of the triple
- predicate: The predicate of the triple
- object: The object of the triple
- modality: Modalities associated with the triples with their counts. TBC means the object can be further refined to the listed objects
- is_negative: 1 if the statement was negated
- score: salience score of the supervised scoring model
- local sigma: strict conditional probability of observing a (predicate, object) with a specific subject. I.e., a measure of how unique a statement is. E.g., local_sigma(lawyers, defend, serial_killers) = 1, local_sigma(lawyers, make, money) = 0.01, even though both statements have a similar score of 0.99. ## Dataset Creation

See original paper. ## Additional Information ### Licensing Information

CC-BY 2.0



Romero et al., Commonsense Properties from Query Logs and Question Answering Forums, CIKM, 2019