
# Dataset Card for Gutenberg Poem Dataset

## 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:** N/A
- **Repository:** [GitHub](https://github.com/google-research-datasets/poem-sentiment)
- **Paper:** [Investigating Societal Biases in a Poetry Composition System](https://arxiv.org/abs/2011.02686)
- **Leaderboard:** N/A
- **Point of Contact:** -

### Dataset Summary

Poem Sentiment is a sentiment dataset of poem verses from Project Gutenberg.
This dataset can be used for tasks such as sentiment classification or style transfer for poems.

### Supported Tasks and Leaderboards

[More Information Needed]

### Languages

The text in the dataset is in English (`en`).

## Dataset Structure

### Data Instances
Example of one instance in the dataset.

```{'id': 0, 'label': 2, 'verse_text': 'with pale blue berries. in these peaceful shades--'}```

### Data Fields

- `id`: index of the example
- `verse_text`: The text of the poem verse
- `label`: The sentiment label. Here
    - 0 = negative
    - 1 = positive
    - 2 = no impact
    - 3 = mixed (both negative and positive)
> Note: The original dataset uses different label indices  (negative = -1, no impact = 0, positive = 1)

### Data Splits

The dataset is split into a `train`, `validation`, and `test` split with the following sizes:

|                    | train | validation | test |
|--------------------|------:|-----------:|-----:|
| Number of examples |   892 |        105 |  104 |



[More Information Needed]
## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

[More Information Needed]

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

[More Information Needed]

#### 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

This work is licensed under a Creative Commons Attribution 4.0 International License

### Citation Information

```
@misc{sheng2020investigating,
      title={Investigating Societal Biases in a Poetry Composition System},
      author={Emily Sheng and David Uthus},
      year={2020},
      eprint={2011.02686},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```

### Contributions

Thanks to [@patil-suraj](https://github.com/patil-suraj) for adding this dataset.
task_categories:text-classification task_ids:sentiment-classification annotations_creators:expert-generated language_creators:found multilinguality:monolingual size_categories:1K<n<10K source_datasets:original language:en license:cc-by-4.0 arxiv:2011.02686 region:us
{"annotations_creators": ["expert-generated"], "language_creators": ["found"], "language": ["en"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["sentiment-classification"], "paperswithcode_id": "gutenberg-poem-dataset", "pretty_name": "Gutenberg Poem Dataset", "dataset_info": {"features": [{"name": "id", "dtype": "int32"}, {"name": "verse_text", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "negative", "1": "positive", "2": "no_impact"}}}}], "splits": [{"name": "train", "num_bytes": 48555, "num_examples": 892}, {"name": "validation", "num_bytes": 5788, "num_examples": 105}, {"name": "test", "num_bytes": 5588, "num_examples": 104}], "download_size": 49870, "dataset_size": 59931}, "train-eval-index": [{"config": "default", "task": "text-classification", "task_id": "multi_class_classification", "splits": {"train_split": "train", "eval_split": "test"}, "col_mapping": {"verse_text": "text", "label": "target"}, "metrics": [{"type": "accuracy", "name": "Accuracy"}, {"type": "f1", "name": "F1 macro", "args": {"average": "macro"}}, {"type": "f1", "name": "F1 micro", "args": {"average": "micro"}}, {"type": "f1", "name": "F1 weighted", "args": {"average": "weighted"}}, {"type": "precision", "name": "Precision macro", "args": {"average": "macro"}}, {"type": "precision", "name": "Precision micro", "args": {"average": "micro"}}, {"type": "precision", "name": "Precision weighted", "args": {"average": "weighted"}}, {"type": "recall", "name": "Recall macro", "args": {"average": "macro"}}, {"type": "recall", "name": "Recall micro", "args": {"average": "micro"}}, {"type": "recall", "name": "Recall weighted", "args": {"average": "weighted"}}]}]}
TAGS
#task_categories-text-classification #task_ids-sentiment-classification #annotations_creators-expert-generated #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-original #language-English #license-cc-by-4.0 #arxiv-2011.02686 #region-us 

Dataset Card for Gutenberg Poem Dataset
=======================================


Table of Contents
-----------------


* Dataset Description
	+ Dataset Summary
	+ Supported Tasks and Leaderboards
	+ 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
	+ Contributions


Dataset Description
-------------------


* Homepage: N/A
* Repository: GitHub
* Paper: Investigating Societal Biases in a Poetry Composition System
* Leaderboard: N/A
* Point of Contact: -


### Dataset Summary


Poem Sentiment is a sentiment dataset of poem verses from Project Gutenberg.
This dataset can be used for tasks such as sentiment classification or style transfer for poems.


### Supported Tasks and Leaderboards


### Languages


The text in the dataset is in English ('en').


Dataset Structure
-----------------


### Data Instances


Example of one instance in the dataset.


### Data Fields


* 'id': index of the example
* 'verse\_text': The text of the poem verse
* 'label': The sentiment label. Here
	+ 0 = negative
	+ 1 = positive
	+ 2 = no impact
	+ 3 = mixed (both negative and positive)



> 
> Note: The original dataset uses different label indices (negative = -1, no impact = 0, positive = 1)
> 
> 
> 


### Data Splits


The dataset is split into a 'train', 'validation', and 'test' split with the following sizes:



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


This work is licensed under a Creative Commons Attribution 4.0 International License


### Contributions


Thanks to @patil-suraj for adding this dataset.



### Dataset Summary


Poem Sentiment is a sentiment dataset of poem verses from Project Gutenberg.
This dataset can be used for tasks such as sentiment classification or style transfer for poems. ### Supported Tasks and Leaderboards ### Languages


The text in the dataset is in English ('en').


Dataset Structure
----------------- ### Data Instances


Example of one instance in the dataset. ### Data Fields


* 'id': index of the example
* 'verse\_text': The text of the poem verse
* 'label': The sentiment label. Here
	+ 0 = negative
	+ 1 = positive
	+ 2 = no impact
	+ 3 = mixed (both negative and positive)



> 
> Note: The original dataset uses different label indices (negative = -1, no impact = 0, positive = 1)
> 
> 
> ### Data Splits


The dataset is split into a 'train', 'validation', and 'test' split with the following sizes:



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


This work is licensed under a Creative Commons Attribution 4.0 International License ### Contributions


Thanks to @patil-suraj for adding this dataset.
TAGS
#task_categories-text-classification #task_ids-sentiment-classification #annotations_creators-expert-generated #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-original #language-English #license-cc-by-4.0 #arxiv-2011.02686 #region-us 
 ### Dataset Summary


Poem Sentiment is a sentiment dataset of poem verses from Project Gutenberg.
This dataset can be used for tasks such as sentiment classification or style transfer for poems. ### Supported Tasks and Leaderboards ### Languages


The text in the dataset is in English ('en').


Dataset Structure
----------------- ### Data Instances


Example of one instance in the dataset. ### Data Fields


* 'id': index of the example
* 'verse\_text': The text of the poem verse
* 'label': The sentiment label. Here
	+ 0 = negative
	+ 1 = positive
	+ 2 = no impact
	+ 3 = mixed (both negative and positive)



> 
> Note: The original dataset uses different label indices (negative = -1, no impact = 0, positive = 1)
> 
> 
> ### Data Splits


The dataset is split into a 'train', 'validation', and 'test' split with the following sizes:



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


This work is licensed under a Creative Commons Attribution 4.0 International License ### Contributions


Thanks to @patil-suraj for adding this dataset.