---
dataset_info:
  features:
    - name: semantic
      dtype: float64
    - name: semantic_rank
      dtype: float64
    - name: semantic_diff
      dtype: float64
    - name: lexical1
      dtype: float64
    - name: lexical1_rank
      dtype: float64
    - name: lexical1_diff
      dtype: float64
    - name: lexical2
      dtype: float64
    - name: lexical2_rank
      dtype: float64
    - name: lexical2_diff
      dtype: float64
    - name: entity
      dtype: string
    - name: src_entity
      dtype: string
    - name: phonetic
      dtype: bool
    - name: pos
      dtype: string
    - name: label
      dtype: bool
  splits:
    - name: train
      num_examples: 19405
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train.csv
license: mit
task_categories:
  - text-classification
language:
  - ar
size_categories:
  - 10K<n<100K
---

# Masrad Dataset

## Dataset Description

The **Masrad** dataset contains 19,405 examples with features related to semantic similarity, lexical similarity, entity recognition, phonetic matching, and part-of-speech tagging for Arabic text.

## Features

| Feature | Type | Description |
|---------|------|-------------|
| `semantic` | float | Semantic similarity score |
| `semantic_rank` | float | Rank based on semantic similarity |
| `semantic_diff` | float | Difference from top semantic score |
| `lexical1` | float | First lexical similarity score |
| `lexical1_rank` | float | Rank based on first lexical score |
| `lexical1_diff` | float | Difference from top first lexical score |
| `lexical2` | float | Second lexical similarity score |
| `lexical2_rank` | float | Rank based on second lexical score |
| `lexical2_diff` | float | Difference from top second lexical score |
| `entity` | string | Detected entity type (PER, ORG, LOC, none) |
| `src_entity` | string | Source entity type |
| `phonetic` | bool | Whether phonetic match exists |
| `pos` | string | Part of speech tag |
| `label` | bool | Target label |

## Usage

```python
from datasets import load_dataset

dataset = load_dataset("U4RASD/Masrad")
```