
# Dataset Card for text2log

## 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:**
- **Repository:** [GitHub](https://github.com/alevkov/text2log)
- **Paper:**
- **Leaderboard:**
- **Point of Contact:** https://github.com/alevkov

### Dataset Summary

The dataset contains 100,000 simple English sentences selected and filtered from `enTenTen15` and their translation into First Order Logic (FOL) using `ccg2lambda`.

### Supported Tasks and Leaderboards

'semantic-parsing': The data set is used to train models which can generate FOL statements from natural language text

### Languages

en-US

## Dataset Structure

### Data Instances

```
{
'clean':'All things that are new are good.',
'trans':'all x1.(_thing(x1) -> (_new(x1) -> _good(x1)))'
}
```

### Data Fields

- 'clean': a simple English sentence
- 'trans': the corresponding translation into Lambda Dependency-based Compositional Semantics 

### Data Splits

No predefined train/test split is given. The authors used a 80/20 split

## Dataset Creation

### Curation Rationale

The text2log data set is used to improve FOL statement generation from natural text

### Source Data

#### Initial Data Collection and Normalization

Short text samples selected from enTenTen15

#### Who are the source language producers?

See https://www.sketchengine.eu/ententen-english-corpus/

### Annotations

#### Annotation process

Machine generated using https://github.com/mynlp/ccg2lambda

#### Who are the annotators?

none

### Personal and Sensitive Information

The dataset does not contain personal or sensitive 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

None given

### Citation Information
```bibtex
@INPROCEEDINGS{9401852, 
author={Levkovskyi, Oleksii and Li, Wei},
booktitle={SoutheastCon 2021},
title={Generating Predicate Logic Expressions from Natural Language},
year={2021},
volume={},
number={},
pages={1-8},
doi={10.1109/SoutheastCon45413.2021.9401852}
}
```

### Contributions

Thanks to [@apergo-ai](https://github.com/apergo-ai) for adding this dataset.
task_categories:translation annotations_creators:machine-generated language_creators:machine-generated multilinguality:monolingual size_categories:100K<n<1M source_datasets:original language:en license:unknown region:us
{"annotations_creators": ["machine-generated"], "language_creators": ["machine-generated"], "language": ["en"], "license": ["unknown"], "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "source_datasets": ["original"], "task_categories": ["translation"], "task_ids": [], "pretty_name": "text2log", "dataset_info": {"features": [{"name": "sentence", "dtype": "string"}, {"name": "fol_translation", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 10358134, "num_examples": 101931}], "download_size": 9746473, "dataset_size": 10358134}}
TAGS
#task_categories-translation #annotations_creators-machine-generated #language_creators-machine-generated #multilinguality-monolingual #size_categories-100K<n<1M #source_datasets-original #language-English #license-unknown #region-us 


# Dataset Card for text2log

## 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:
- Repository: GitHub
- Paper:
- Leaderboard:
- Point of Contact: URL

### Dataset Summary

The dataset contains 100,000 simple English sentences selected and filtered from 'enTenTen15' and their translation into First Order Logic (FOL) using 'ccg2lambda'.

### Supported Tasks and Leaderboards

'semantic-parsing': The data set is used to train models which can generate FOL statements from natural language text

### Languages

en-US

## Dataset Structure

### Data Instances



### Data Fields

- 'clean': a simple English sentence
- 'trans': the corresponding translation into Lambda Dependency-based Compositional Semantics 

### Data Splits

No predefined train/test split is given. The authors used a 80/20 split

## Dataset Creation

### Curation Rationale

The text2log data set is used to improve FOL statement generation from natural text

### Source Data

#### Initial Data Collection and Normalization

Short text samples selected from enTenTen15

#### Who are the source language producers?

See URL

### Annotations

#### Annotation process

Machine generated using URL

#### Who are the annotators?

none

### Personal and Sensitive Information

The dataset does not contain personal or sensitive information.

## Considerations for Using the Data

### Social Impact of Dataset



### Discussion of Biases



### Other Known Limitations



## Additional Information

### Dataset Curators



### Licensing Information

None given




### Contributions

Thanks to @apergo-ai for adding this dataset.
# Dataset Card for text2log ## 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:
- Repository: GitHub
- Paper:
- Leaderboard:
- Point of Contact: URL ### Dataset Summary

The dataset contains 100,000 simple English sentences selected and filtered from 'enTenTen15' and their translation into First Order Logic (FOL) using 'ccg2lambda'. ### Supported Tasks and Leaderboards

'semantic-parsing': The data set is used to train models which can generate FOL statements from natural language text ### Languages

en-US ## Dataset Structure ### Data Instances ### Data Fields

- 'clean': a simple English sentence
- 'trans': the corresponding translation into Lambda Dependency-based Compositional Semantics ### Data Splits

No predefined train/test split is given. The authors used a 80/20 split ## Dataset Creation ### Curation Rationale

The text2log data set is used to improve FOL statement generation from natural text ### Source Data #### Initial Data Collection and Normalization

Short text samples selected from enTenTen15 #### Who are the source language producers?

See URL ### Annotations #### Annotation process

Machine generated using URL #### Who are the annotators?

none ### Personal and Sensitive Information

The dataset does not contain personal or sensitive information. ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations ## Additional Information ### Dataset Curators ### Licensing Information

None given ### Contributions

Thanks to @apergo-ai for adding this dataset.
TAGS
#task_categories-translation #annotations_creators-machine-generated #language_creators-machine-generated #multilinguality-monolingual #size_categories-100K<n<1M #source_datasets-original #language-English #license-unknown #region-us 
 # Dataset Card for text2log ## 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:
- Repository: GitHub
- Paper:
- Leaderboard:
- Point of Contact: URL ### Dataset Summary

The dataset contains 100,000 simple English sentences selected and filtered from 'enTenTen15' and their translation into First Order Logic (FOL) using 'ccg2lambda'. ### Supported Tasks and Leaderboards

'semantic-parsing': The data set is used to train models which can generate FOL statements from natural language text ### Languages

en-US ## Dataset Structure ### Data Instances ### Data Fields

- 'clean': a simple English sentence
- 'trans': the corresponding translation into Lambda Dependency-based Compositional Semantics ### Data Splits

No predefined train/test split is given. The authors used a 80/20 split ## Dataset Creation ### Curation Rationale

The text2log data set is used to improve FOL statement generation from natural text ### Source Data #### Initial Data Collection and Normalization

Short text samples selected from enTenTen15 #### Who are the source language producers?

See URL ### Annotations #### Annotation process

Machine generated using URL #### Who are the annotators?

none ### Personal and Sensitive Information

The dataset does not contain personal or sensitive information. ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations ## Additional Information ### Dataset Curators ### Licensing Information

None given ### Contributions

Thanks to @apergo-ai for adding this dataset.