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---
dataset_info:
features:
- name: query_id
dtype: int64
- name: rel_score
dtype: int64
- name: doc_id
dtype: int64
- name: query
dtype: string
- name: document
dtype: string
splits:
- name: train
num_bytes: 325495
num_examples: 999
download_size: 108552
dataset_size: 325495
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# 🎲 LudoSym: Gambling Addiction IR Dataset (Spanish)
## Overview
This dataset accompanies the paper:
**Analyzing Gambling Addictions: A Spanish Corpus for Understanding Pathological Behavior**
Manuel Couto-Pintos, Marcos Fernández-Pichel, Mario Ezra Aragón, David E. Losada
*Findings of the Association for Computational Linguistics: EMNLP 2025*
The dataset is designed to support **information retrieval and ranking research** focused on the detection and analysis of **gambling addiction symptoms** from Spanish text. It enables the evaluation and training of retrieval models that associate user-defined symptom queries with relevant textual evidence.
---
## Task Description
The dataset follows a **standard IR / ranking formulation**:
- **Queries** represent standardized gambling addiction symptoms.
- **Documents** are short Spanish text passages related to gambling behavior.
- **Relevance judgments (qrels)** indicate how relevant each document is for a given symptom query.
The task is to **rank documents by relevance for each query**, enabling:
- neural ranking
- symptom screening
- cross-encoder and bi-encoder training
- IR evaluation (e.g., nDCG, MAP, Recall)
---
## Dataset Structure
Each example in the dataset has the following fields:
| Field | Type | Description |
|------------|---------|-------------|
| `query_id` | int | Unique identifier of the symptom query |
| `doc_id` | int | Unique identifier of the document |
| `query` | string | Text of the gambling addiction symptom |
| `document` | string | Spanish text passage |
| `relevance`| float | Relevance score between the query and the document |
## Citation
If you use this resource, please cite:
```
@inproceedings{couto-etal-2025,
title = "Analyzing Gambling Addictions: A Spanish Corpus for Understanding Pathological Behavior",
author = "Couto-Pintos, Manuel and
Fernández-Pichel, Marcos and
Aragón, Mario Ezra and
Losada, David E.",
booktitle = "Findings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP)"
}
```