| --- |
| license: odc-by |
| configs: |
| - config_name: de |
| data_files: |
| - split: train |
| path: de/train-* |
| - config_name: es |
| data_files: |
| - split: train |
| path: es/train-* |
| - config_name: fr |
| data_files: |
| - split: train |
| path: fr/train-* |
| - config_name: it |
| data_files: |
| - split: train |
| path: it/train-* |
| dataset_info: |
| - config_name: de |
| features: |
| - name: id |
| dtype: string |
| - name: category |
| dtype: string |
| - name: instruction |
| dtype: string |
| - name: context |
| dtype: string |
| - name: response |
| dtype: string |
| - name: lang |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 1554543 |
| num_examples: 2541 |
| download_size: 968090 |
| dataset_size: 1554543 |
| - config_name: es |
| features: |
| - name: id |
| dtype: string |
| - name: category |
| dtype: string |
| - name: instruction |
| dtype: string |
| - name: context |
| dtype: string |
| - name: response |
| dtype: string |
| - name: lang |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 1498790 |
| num_examples: 2552 |
| download_size: 950039 |
| dataset_size: 1498790 |
| - config_name: fr |
| features: |
| - name: id |
| dtype: string |
| - name: category |
| dtype: string |
| - name: instruction |
| dtype: string |
| - name: context |
| dtype: string |
| - name: response |
| dtype: string |
| - name: lang |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 1503595 |
| num_examples: 2534 |
| download_size: 937468 |
| dataset_size: 1503595 |
| - config_name: it |
| features: |
| - name: id |
| dtype: string |
| - name: category |
| dtype: string |
| - name: instruction |
| dtype: string |
| - name: context |
| dtype: string |
| - name: response |
| dtype: string |
| - name: lang |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 1474583 |
| num_examples: 2548 |
| download_size: 953876 |
| dataset_size: 1474583 |
| task_categories: |
| - question-answering |
| - text-classification |
| - summarization |
| - text-generation |
| language: |
| - fr |
| - de |
| - it |
| - es |
| size_categories: |
| - 10K<n<100K |
| --- |
| # Multilingual MentorES Dataset |
|
|
| ## Overview |
|
|
| **Multilingual MentorES** is a **multilingual** version of the Spanish-language dataset [MentorES](https://huggingface.co/datasets/projecte-aina/MentorES). The original MentorES dataset is a manually curated, open-source dataset for instruction-tuning of Large Language Models. The following tasks are represented in the dataset: closed QA, open QA, general QA, classification, information extraction, summarization, creative writing and brainstorming. |
|
|
| The multilingual version was obtained by translating parts of the original dataset respectively into **French**, **German** and **Italian**. The models used for translation were **Qwen3-VL-235B-A22B-Instruct** for French and Italian, **Mistral-Small-3.1-24B-Instruct** for German. Both models have **permissive licenses** that allow reuse of their output for a variety of purposes. |
|
|
| ## Language Distribution |
|
|
| The original dataset contains 10,175 instructions. They were divided equally among the four represented languages, making sure to also balance the number of examples for each task across languages. The final distribution is as follows: |
|
|
| | Language | Subset Name | Percentage | Number of Examples | |
| |----------|------------ |------------|--------------------| |
| | Italian | it | 25% | 2,548 | |
| | French | fr | 25% | 2,534 | |
| | Spanish | es | 25% | 2,552 | |
| | German | de | 25% | 2,541 | |
|
|
| ## Further processing |
|
|
| During the translation phase, language experts noticed **localization** issues in the models' output. The original dataset is understandably focused on Spanish culture and language, and the translation models sometimes could not correctly transpose the examples into the target language. This was often the case with instructions regarding aspects of the Spanish language (e.g. "List all words containing ñ in the following paragraph"), or references to Spanish titles of books, movies, plays, etc. |
|
|
| We isolated these problematic entries using keywords and proceeded to do a **manual review** of localization across the translated portions of the dataset. Overall the review involved about 450 instructions each for German, French and Italian. |
|
|
| ### Dataset Structure |
|
|
| Each entry contains the following **fields**: |
|
|
| | Field | Type | Description | |
| | ------- | ------ | ------------- | |
| | `id` | string | Unique index of the instruction | |
| | `category` | string | Type of task (QA, summarization, writing, etc) | |
| | `instruction` | string | Text of the instruction | |
| | `context` | string | Context provided to the assistant as support information | |
| | `response` | string | Text of the response | |
| | `lang` | string | Language of the entry | |
|
|
| ## Licensing |
|
|
| The dataset is distributed under the **ODC-BY-1.0** license. |
| Users must adhere to the attribution and usage requirements outlined under this license. |
|
|
