---
annotations_creators:
- found
language_creators:
- found
language:
- ca
license:
- cc-by-nc-nd-4.0
multilinguality:
- monolingual
pretty_name: GuiaCat
size_categories:
- ?
task_categories:
- text-classification
task_ids:
- sentiment-classification
- sentiment-scoring
---

# Dataset Card for GuiaCat

## 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)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [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

- **Point of Contact:** [blanca.calvo@bsc.es](blanca.calvo@bsc.es)

### Dataset Summary

TODO

### Supported Tasks and Leaderboards

This corpus is mainly intended for sentiment analysis.

### Languages

The dataset is in Catalan (`ca-CA`).

## Dataset Structure

The dataset consists of restaurant reviews labelled with 5 scores: service, food, price-quality, environment, and average. Reviews also have a sentiment label, derived from the average score. It's a csv file. 

### Data Instances

  |  service  |  food  |  price-quality  |  environment  |  avg  | text | label |
 | ------- | ---- | ------------ | ------------ | ----- | 
 | 8 | 8 | 8 | 8 | 8.0 | Bon Menjar i bon tracte en un restaurant que segú hi tornaràs un altre vegada. | molt bo |
| 8 |7 |9|7|7.8|Fa anys que hi anem de tant en tant. Pel meu gust és dels millors que conec en qualitat-preu. És mes aviat econòmic amb qualitat. Són gent molt amable i trempada. Ideal anar-hi a dinar en tornar de fer alguna excursió a peu o en bicicleta. Hi ha força varietat de plats. M'agrada especialmente la seva escudella i el senglar durant la temporada de caça. | bo |
 

### Data Fields
- service: a score from 0 to 10 grading the service
- food: a score from 0 to 10 grading the food
- price-quality: a score from 0 to 10 grading the relation between price and quality
- environment: a score from 0 to 10 grading the environment
- avg: average of all the scores
- text: the review
- label: it can be "molt bo", "bo", "regular", "dolent", "molt dolent"

### Data Splits

* dev.csv: 500 examples
* test.csv: 500 examples
* train.csv: 4750 examples

## Dataset Creation

### Curation Rationale

We created this corpus to contribute to the development of language models in Catalan, a low-resource language. 

### Source Data

The data of this dataset has been provided by [GuiaCat](https://guiacat.cat).

#### Initial Data Collection and Normalization

NA

#### Who are the source language producers?

The language producers were the users from Guiacat.

### Annotations

The annotations are automatically derived from the scores that the users provided while reviewing the restaurants.

#### Annotation process

The mapping between average scores and labels is:
- Higher than 8: molt bo
- Between 8 and 6: bo
- Between 6 and 4: regular
- Between 4 and 2: dolent
- Less than 2: molt dolent

#### Who are the annotators?

Users

### Personal and Sensitive Information

No personal information included, although it could contain hate or abusive language.

## Considerations for Using the Data

### Social Impact of Dataset

We hope this corpus contributes to the development of language models in Catalan, a low-resource language.

### Discussion of Biases

We are aware that this data might contain biases. We have not applied any steps to reduce their impact.

### Other Known Limitations

[N/A]

## Additional Information

### Dataset Curators

Blanca Calvo Figueras, Barcelona Supercomputing Center (blanca.calvo@bsc.es)


### Licensing Information

[Creative Commons Attribution Non-commercial No-Derivatives 4.0 International](https://creativecommons.org/licenses/by-nc-nd/4.0/).

### Citation Information

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### Contributions

We want to thank Guiacat for providing this data.

### Funding

This work was funded by the [Catalan Ministry of the Vice-presidency, Digital Policies and Territory](https://politiquesdigitals.gencat.cat/en/inici/index.html) within the framework of the [Aina project](https://politiquesdigitals.gencat.cat/ca/tic/aina-el-projecte-per-garantir-el-catala-en-lera-digital/).