Datasets:

BeitTigreAI
/

tigre-data-parallel-multilingual

@@ -6,13 +6,68 @@ task_categories:
 - translation
 ---
-### Python Script
 ```python
 from datasets import load_dataset
 import pandas as pd
-# Load dataset from Hugging Face Hub
 dataset = load_dataset(
     "BeitTigreAI/tigre-data-parallel-multilingual",
     data_files={
@@ -21,47 +76,22 @@ dataset = load_dataset(
     }
 )
-# Print dataset info
-print("📊 Dataset Info:")
 print(dataset)
-# Convert to pandas for easy analysis
-print("\n🔍 Number of samples per target language:")
-for split in ["train", "validation"]:
-    print(f"\n➡️  {split.title()} Split:")
-    df = dataset[split].to_pandas()
-    # Count by tgt_lang
-    lang_counts = df["tgt_lang"].value_counts().to_frame().reset_index()
-    lang_counts.columns = ["tgt_lang", "count"]
-    lang_counts["percentage"] = (lang_counts["count"] / lang_counts["count"].sum() * 100).round(2)
-    # Print as table
-    print(lang_counts.to_string(index=False))
-# Database Summary Statistics
-**Total Sentences in Corpus:** 329,554
-## Language Pair Distribution and Metrics
-| Target Language   | Total Sentences   | Percentage   | Total Source Words (Tigre)   | Avg Src Words/Sentence (Tigre)   | Total Target Words   | Avg Tgt Words/Sentence   | Total Source Characters (Tigre)   | Total Target Characters   |
-|:------------------|:------------------|:-------------|:-----------------------------|:---------------------------------|:---------------------|:-------------------------|:----------------------------------|:--------------------------|
-| ara_Arab          | 49,964            | 15.16        | 172,645                      | 3.46                             | 160,675              | 3.22                     | 708,105                           | 826,492                   |
-| deu_Latn          | 80,120            | 24.31        | 258,160                      | 3.22                             | 321,966              | 4.02                     | 1,052,740                         | 1,806,555                 |
-| eng_Latn          | 156,206           | 47.4         | 508,318                      | 3.25                             | 610,321              | 3.91                     | 2,070,639                         | 3,111,863                 |
-| nno_Latn          | 6,001             | 1.82         | 14,055                       | 2.34                             | 14,619               | 2.44                     | 56,798                            | 73,000                    |
-| nob_Latn          | 8,222             | 2.49         | 21,567                       | 2.62                             | 23,481               | 2.86                     | 86,756                            | 118,104                   |
-| swe_Latn          | 28,554            | 8.66         | 96,439                       | 3.38                             | 107,562              | 3.77                     | 396,387                           | 547,444                   |
-| tir_Ethi          | 487               | 0.15         | 1,767                        | 3.63                             | 1,783                | 3.66                     | 7,387                             | 7,754                     |
-## Corpus Grand Totals
-- Total Source Words (Tigre): 1,072,951
-- Total Target Words: 1,240,407
-- Total Source Characters (Tigre): 4,378,812
-- Total Target Characters: 6,491,212
-- Overall Average Sentence Length (Source): 3.26 words
-- Overall Average Sentence Length (Target): 3.76 words

 - translation
 ---
+# Tigre Parallel Multilingual Dataset (Tigre-Data 1.0)
+## Overview
+This repository introduces the **Parallel Multilingual Text** component of the Tigre language resource collection. Tigre is an under-resourced South Semitic language within the Afro-Asiatic family.
+The goal of **Tigre-Data 1.0** is to accelerate research in low-resource NLP and morphologically rich language modeling. This dataset provides a clean, high-quality parallel corpus essential for developing and evaluating **Machine Translation (MT)** systems for Tigre.
+### Data Source & Licensing
+The parallel sentences in this dataset originate from Tatoeba.org, a community-driven multilingual corpus released under the CC-BY 2.0 license. All Tigre translations were contributed by native-speaking members of the Tigre diaspora, reflecting years of collective volunteer effort to expand the language’s digital presence. This contribution is significant, as, by the end of 2025, the Tigre language on Tatoeba.org is supported by 77 registered translators working across more than ten other languages, resulting in a larger sentence pool than 93% of the 429 hosted languages.
+## Included Data & Structure
+### Data Modalities
+This repository contains the **Parallel Multilingual Text** modality.
+The corresponding **Monolingual Text** dataset is available in a separate repository.
+### Dataset Structure
+The dataset is provided in **Parquet format**, compatible with the Hugging Face `datasets` library.
+```text
+tigre-data-parallel-multilingual/
+├── README.md
+└── tigre-data-parallel-multilingual.parquet
+```
+## Dataset Statistics and Metrics
+The dataset contains **329,554 parallel sentences** across seven target languages.
+### Corpus Totals
+| Statistic                    | Value      |
+| ---------------------------- | ---------- |
+| Total Sentences in Corpus    | 329,554    |
+| Total Source Words (Tigre)   | 1,072,951  |
+| Total Target Words           | 1,240,407  |
+| Avg Sentence Length (Tigre)  | 3.26 words |
+| Avg Sentence Length (Target) | 3.76 words |
+### Language Pair Distribution (Tigre → Target Language)
+| Target Language              | Total Sentences | Percentage | Tigre Words | Avg Src Words/Sentence | Target Words | Avg Tgt Words/Sentence |
+| ---------------------------- | --------------- | ---------- | ----------- | ---------------------- | ------------ | ---------------------- |
+| ara_Arab (Arabic)            | 49,964          | 15.16%     | 172,645     | 3.46                   | 160,675      | 3.22                   |
+| deu_Latn (German)            | 80,120          | 24.31%     | 258,160     | 3.22                   | 321,966      | 4.02                   |
+| eng_Latn (English)           | 156,206         | 47.40%     | 508,318     | 3.25                   | 610,321      | 3.91                   |
+| nno_Latn (Norwegian Nynorsk) | 6,001           | 1.82%      | 14,055      | 2.34                   | 14,619       | 2.44                   |
+| nob_Latn (Norwegian Bokmål)  | 8,222           | 2.49%      | 21,567      | 2.62                   | 23,481       | 2.86                   |
+| swe_Latn (Swedish)           | 28,554          | 8.66%      | 96,439      | 3.38                   | 107,562      | 3.77                   |
+| tir_Ethi (Tigrinya)          | 487             | 0.15%      | 1,767       | 3.63                   | 1,783        | 3.66                   |
+## How to Download & Load the Dataset
 ```python
 from datasets import load_dataset
 import pandas as pd
 dataset = load_dataset(
     "BeitTigreAI/tigre-data-parallel-multilingual",
     data_files={
     }
 )
+print("Dataset Info:")
 print(dataset)
+df_train = dataset["train"].to_pandas()
+lang_counts = df_train["tgt_lang"].value_counts().to_frame().reset_index()
+lang_counts.columns = ["tgt_lang", "count"]
+lang_counts["percentage"] = (lang_counts["count"] / lang_counts["count"].sum() * 100).round(2)
+print(lang_counts.to_string(index=False))
+```
+## Licensing
+This dataset is released under the CC-BY-SA-4.0 license.
+## Citation
+If you use this resource, please cite the dataset using its Hugging Face entry.
+Repository: Tigre Parallel Multilingual Dataset
+Organization: BeitTigreAI
+URL: https://huggingface.co/datasets/BeitTigreAI/tigre-data-parallel-multilingual