crodri/meteocat

---
language:
- ca
multilinguality:
- monolingual
pretty_name: synthetic_meteocat
size_categories:
- 10K<n<100K
task_categories:
- text-generation
- token-classification
- question-answering
task_ids:
- named-entity-recognition
---

# Dataset Card for Meteocat

## 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)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)

## Dataset Description

- **Point of Contact:** [[e-mail]]([e-mail])

### Dataset Summary

This is a synthetic dataset that contains examples, each of them, with the following fields:
- Instructions like "El dissabte a la nit, quin temps farà a Mont-real?"
- Context like "Day: dissabte | Location: Mont-real | mati: el cel estarà molt ennuvolat | tarda: plourà escadusserament | nit: el cel tendirà a estar cobert de núvols | temp: Lleugera pujada de les temperatures"
- Response like "A la nit el cel estarà ennuvolat"

Added instructions for answering "yes" or "no" questions.

### Supported Tasks and Leaderboards

This dataset is mainly intended to train models for text-generation and named-entity-recognition.

### Languages

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

## Dataset Structure

The dataset consists of examples in a jsonl format with 3 fields each: instruction, context and response.

### Data Instances
Changed origina context for a more linguistically natural one: "tarda del divendres a Montesquiu al mati s'esperen més nuvolades, a la tarda guspirejarà amb insistència, a la nit podria guspirejar, i Temperatures sense canvis"
{
"instruction": "Quin temps farà a la nit a Camarasa dijous?",
xxx "context": "Day: dijous | Location: Camarasa | mati: el cel anirà encapotant-se cada cop més | tarda: el sol anirà guanyant terreny als núvols | nit: cel clar | temp: Temperatures sense canvis",
"response": "A la nit, cel ben clar"
}

### Data Fields
- instruction: Weather-related question.
xxx - context: Information in the format "Day: [DAY] | Location: [LOCATION] | mati: [WEATHER FORECAST] | tarda: [WEATHER FORECAST] | nit: [WEATHER FORECAST]".

- response: Whether forecast answering the question.

### Data Splits

* dev.json: 6873 examples
* test.json: 1279 examples
* train.json: 61776 examples

## Additional Information

### Dataset Curators

Text Mining Unit (TeMU) at the Barcelona Supercomputing Center ([e-mail])

This work was funded by the [Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya](https://politiquesdigitals.gencat.cat/ca/inici/index.html#googtrans(ca|en) within the framework of [Projecte AINA](https://politiquesdigitals.gencat.cat/ca/economia/catalonia-ai/aina).

### Licensing Information

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

### Contributions

[N/A]

原始信息汇总

数据集卡片 for Meteocat

数据集描述

数据集摘要

这是一个合成数据集，包含以下字段：

• 指令，例如 "El dissabte a la nit, quin temps farà a Mont-real?"
• 上下文，例如 "Day: dissabte | Location: Mont-real | mati: el cel estarà molt ennuvolat | tarda: plourà escadusserament | nit: el cel tendirà a estar cobert de núvols | temp: Lleugera pujada de les temperatures"
• 响应，例如 "A la nit el cel estarà ennuvolat"

增加了回答 "是" 或 "否" 问题的指令。

支持的任务和排行榜

该数据集主要用于训练文本生成和命名实体识别模型。

语言

该数据集使用加泰罗尼亚语 (ca-CA)。

数据集结构

数据集由包含三个字段的 jsonl 格式示例组成：指令、上下文和响应。

数据实例

原始上下文已更改为更符合语言自然性的内容："tarda del divendres a Montesquiu al mati sesperen més nuvolades, a la tarda guspirejarà amb insistència, a la nit podria guspirejar, i Temperatures sense canvis" json { "instruction": "Quin temps farà a la nit a Camarasa dijous?", "context": "Day: dijous | Location: Camarasa | mati: el cel anirà encapotant-se cada cop més | tarda: el sol anirà guanyant terreny als núvols | nit: cel clar | temp: Temperatures sense canvis", "response": "A la nit, cel ben clar" }

数据字段

• 指令：与天气相关的问题。
• 上下文：格式为 "Day: [DAY] | Location: [LOCATION] | mati: [WEATHER FORECAST] | tarda: [WEATHER FORECAST] | nit: [WEATHER FORECAST]" 的信息。
• 响应：回答问题的天气预报。

数据分割

• dev.json: 6873 个示例
• test.json: 1279 个示例
• train.json: 61776 个示例