metadata

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
Dataset Description
Dataset Structure
Additional Information

Dataset Description

Point of Contact: langtech@bsc.es

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 (bsc-temu@bsc.es)

This work was funded by the Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya within the framework of Projecte AINA.

Licensing Information

???? Creative Commons Attribution Non-commercial No-Derivatives 4.0 International.

Contributions

[N/A]