---
dataset_info:
  features:
  - name: title
    dtype: string
  - name: author
    dtype: string
  - name: id
    dtype: int32
  - name: timestamp
    dtype: string
  - name: progressive_number
    dtype: int32
  - name: original_url
    dtype: string
  - name: newsgroup
    dtype: string
  - name: text
    dtype: string
  splits:
  - name: trainv
    path: parquet/*.parquet
    num_bytes: 72373684017
    num_examples: 85010057
  download_size: 0
  dataset_size: 72373684017
language:
- it
pretty_name: U
---
# Usenet Archive IT Dataset 🇮🇹

## Description

### Dataset Content

This dataset contains Usenet posts from Italian language newsgroups belonging to the `it`, `it-alt` and `italia` hierarchies. The data has been archived and converted to the Parquet format for easy processing. The only preprocessing conducted on the text was the removal of source code of some malicious scripts that were present in the original data and were causing HF to flag the dataset as malicious.

This dataset contributes to the [mii-community](https://huggingface.co/mii-community) project, aimed at advancing the creation of Italian open-source Language Models (LLMs).🇮🇹 🤖

### Descriptive Statistics

This dataset contains 85010057 posts from 11956999 threads in 539 newsgroups. Threads appear to have around 7 posts on average, with a median of 3 posts. 
The posts were created between 1995 and 2024. The text of all the posts together sum up to a total of 55885335313 characters, or approximately 10-20B tokens. The average length of the posts is 657 characters, and the median length is 380 characters.

### Languages

The dataset should contain only Italian language posts, but it is possible that some posts are in other languages. The dataset has not been language filtered, as post were expected to be in Italian.

## Dataset Structure

### Features

Each record in the dataset has the following fields:

- `title`: The title of the post.
- `author`: The username of the author of the post.
- `id`: The unique identifier of the post.
- `timestamp`: The timestamp of the post.
- `progressive_number`: An integer identifying the thread number in the newsgroup.
- `original_url`: The URL of the original post on Google Groups.
- `newsgroup`: The name of the newsgroup the post belongs to.
- `text`: The text content of the post.

This repo contains the dataset in the Parquet format. The dataset is split into multiple Parquet files inside the `parquet` folder, each containing a portion of the records. The files are named `usenet_converted_*.parquet`, where `*` is a number indicating the order of the file.
The original jsonl lines of the data are included as well as compressed bz2 files.

### Example

Below is a complete JSON record for reference:

```json
{"title": "Cerco Vespa", "author": "Castel", "id": 4423, "progressive_number": 1, "timestamp": "1998-06-26T09:00:00", "newsgroup": "it.annunci.usato", "original_url": "https://groups.google.com/g/it.annunci.usato/c/kKlb8hcSiX0/m/eXMsxa8SJ5gJ", "text": "Cerco vespa 125 o 50 in buono stato ma di vecchio modello, zone RE, PR, MO.\nGrazie in anticipo\nCastel\nlorenzo.c...@comune.re.it"}
```



## Additional Information

### Dataset Curators

This dataset was compiled and curated by Hugging Face users [manalog](https://huggingface.co/manalog) and [ruggsea](https://huggingface.co/ruggsea), as part of the [mii-community](https://huggingface.co/mii-community) dataset creation effort.

### Dataset rationale

The dataset was created as part of a bigger effort to create various high-quality datasets of native Italian text, with the aim of aiding the development of Italian open-source LLMs. 

The dataset is expected to be used for training and fine-tuning language models, as well as for other NLP tasks such as text classification, summarization, and translation. The column `text` contains the raw text of the posts, and the column `newsgroup` contains the name of the newsgroup the post belongs to, which can be used for classification tasks.

## Usage

You can load the dataset directly from datasets using the `load_dataset` function. Here's an example:

```python
from datasets import load_dataset

dataset = load_dataset("manalog/UsenetArchiveIT")
```