# Copy of FLARES: Subtask 1 --5W1Hs identification-- — Data

来源：https://www.kaggle.com/competitions/copy-of-flares-identification/data

本地 Meta Kaggle 快照；不是本次实时页面。

# Dataset Description

The dataset contains a total of 570 news items annotated with the journalistic   technique 5W1H, obtaining approximately 19,322 annotations. The dataset has been splitted into a proportion of 70% (13,526) for training, 10% (1,932) for development, and 20% (3,864) for testing. The corpus contains text in Spanish manually annotated with an extraction technique known as 5W1H, which is a journalistic technique consisting of annotating all the entities present in a text related to the questions What, Who, Where, When, Why and How. It was annotated by three expert annotators (2 linguistics and 1 sociologist), all three specialized in NLP and with knowledge in the annotation guideline created for this purpose.
The language chosen is Spanish because, although it is the fourth most widely spoken language in the world and the second mother tongue in the world in terms of number of speakers, there are few corpora built in Spanish to address the automatic reliability detection task in NLP. 

With regard to the domain, the topics covered in this dataset include economy, sports, science, education, health, society, entertainment, politics and security.

Regarding the collection procedure, 170 news was collected manually and via web crawling, while the other 400 news was collected from an existing corpus --- named The Spanish Fake News Corpus (SFN). News was collected from digital newspapers such as ABC, BBC News, CNN Spanish, El Espectador, El Financiero, El Mundo, El País, Huffpost, Marca, La Jornada, El Diestro, Eje21, Periodista Digital, Ok Diario, 20 Minutos, la Vanguardia, among others. For the construction of the dataset, news that did not follow the language, format, extension, or other semantic characteristics desired in the corpus was filtered out.

## Files

*   **5w1h_subtask_1_train.csv** - the training set 1
*   **5w1h_subtask_1_test.json** - the test set