Update Dataset Details

README.md

@@ -47,3 +47,156 @@ configs:
   - split: s5_arqna
     path: data/s5_arqna-*
 ---
+
+# Silma Arabic Triplets Dataset - `v1.0`
+
+
+## Overview
+The **Silma Arabic Triplets Dataset - v1.0** is a high-quality, diverse dataset specifically curated 
+for training and training embedding models for **semantic search** tasks
+in the Arabic language. 
+
+The dataset contains more than `2.25M` records (`2,280,319` records).
+
+This dataset includes triplets in the form of **anchor, positive**, and **negative** samples, designed to enhance models in learning semantic similarity and dissimilarity. 
+
+The dataset consists of **five unique splits** sourced from diverse domains, providing a robust foundation for building Arabic-language models that require nuanced understanding of text relationships.
+
+## Dataset Structure
+The dataset is structured as a `DatasetDict` containing five different sources, each with their own distinct rows and domains:
+
+
+## Splits
+
+Here are descriptions with associated representative examples  from each split of the dataset:
+
+### Split 1: Akhooli
+
+
+**Description:**
+A curated set of the original [akhooli](https://huggingface.co/datasets/akhooli/arabic-triplets-1m-curated-sims-len) associated with a defined negative sample for each record.
+
+**Size**: `1,013,295` samples
+
+**Sample**
+```json
+{
+  "anchor": "صبي صغير وفتاة صغيرة يركبان دراجتيهما على الرصيف مع عجلات مساعدة.",
+  "positive": "فتى وفتاة يتعلمون ركوب الدراجات",
+  "negative": "الصبي الصغير يصل إلى العصا من الفتاة وهو يدير سباق التتابع"
+}
+```
+
+### Split 2: ArabicQuoraDuplicates
+
+
+**Description:**
+A curated set of the original [ArabicQuoraDuplicates](https://huggingface.co/datasets/AbderrahmanSkiredj1/ArabicQuoraDuplicates_stsb_Alue_holyquran_aranli_900k_anchor_positive_negative) source after cleaning and filtering out some outliers.
+
+**Size:** `850,914` samples
+
+**Sample**
+
+```json
+{
+  "anchor": "ثلاثة رجال يلعبون كرة السلة",
+  "positive": "ثلاثة رجال يلعبون لعبة كرة السلة",
+  "negative": "رجلين يرتديان ملابس غريبة يقفزان على ملعب كرة السلة"
+}
+```
+
+### Split 3: WikiMatrix
+
+
+**Description:**
+A curated set of the original [WikiMatrix](https://huggingface.co/datasets/sentence-transformers/parallel-sentences-wikimatrix) associated with a defined negative sample for each record.
+
+**Size**: `222,739` samples
+
+**Sample**
+```json
+{
+  "anchor": "When multi-party elections began in the 1940s, the share of women in the legislature fell, and the 4% share of parliamentary seats gained in 1935 was not reached again until 1999.",
+  "positive": "وعندما بدأت انتخابات الأحزاب المتعددة في الأربعينيات من القرن الماضي، انخفضت حصة المرأة في المجلس التشريعي، ولم يتم التوصل إلى نسبة 4 في المائة من المقاعد البرلمانية التي اكتُسبت في عام 1935 مرة أخرى حتى عام 1999.",
+  "negative": "الانتخابات النيابية والبلدية تجري كل أربع سنوات منذ عودة العمل بالدستور في عام 2002 عندما تم منح المرأة أيضا التصويت لأول مرة كجزء من الإصلاحات الديمقراطية التي تعهد بها الملك حمد."
+}
+```
+
+### Split 4: TedTalks
+
+
+**Description:**
+A curated set of the original [TedTalks2020-en:ar](https://opus.nlpl.eu/TED2020/ar&en/v1/TED2020) associated with a defined negative sample for each record.
+
+**Size**: `192,699` samples
+
+**Sample**
+```json
+{
+  "anchor": "But if we think about it, we are actually recently arrived guests on this planet, the human species.",
+  "positive": "ولكن إذا أمعنا النظر فيها، فسنجد أننا قد وصلنا إلى مرحلة أننا ضيوف على هذا الكوكب، أقصد بذلك الجنس البشري.",
+  "negative": "ولكن إذا أردنا أن نستكشف نهايات حدود هذا الكوكب، علينا أن نعيش هناك."
+}
+```
+
+### Split 5: QnA
+
+**Description:**
+A small QnA Arabic triplets dataset.
+
+**Size**: `672` samples
+
+**Sample**
+```json
+{
+  "anchor": "ما هي منظمة غرب إفريقيا التي تنتمي إليها غينيا كوناكري؟",
+  "positive": "غينيا كوناكري عضو في الأمم المتحدة والجماعة الاقتصادية لدول غرب إفريقيا.",
+  "negative": "أي بلد يبعد حوالي 4200 كم عن غينيا كوناكري؟"
+}
+```
+
+## Column Descriptions
+
+Each dataset in the **Silma Arabic Triplets Dataset - v1.0** contains the following columns:
+
+### `anchor`
+- **Description:** The main reference sentence or query in the triplet. It serves as the anchor point to which the positive and negative samples are compared.
+- **Type:** String
+
+### `positive`
+- **Description:** A sentence that is semantically similar to the anchor sentence. This sentence is the "positive" counterpart that shares meaning or context with the anchor.
+- **Type:** String
+
+### `negative`
+- **Description:** A sentence that is semantically dissimilar to the anchor sentence. It provides contrast by being unrelated in meaning to the anchor.
+- **Type:** String
+
+### `source`
+- **Description:** The source or dataset from which the triplet is derived. This helps identify the domain or origin of the triplet data.
+- **Type:** String
+
+### `anchor_len`
+- **Description:** The number of words or tokens in the anchor sentence. This helps in analyzing sentence length and complexity across the dataset.
+- **Type:** Integer
+
+### `positive_len`
+- **Description:** The number of words or tokens in the positive sentence. This gives insights into the sentence length of semantically similar examples.
+- **Type:** Integer
+
+### `negative_len`
+- **Description:** The number of words or tokens in the negative sentence. This column reflects the length of the dissimilar sentence in the triplet.
+- **Type:** Integer
+
+## Summary
+Each triplet consists of an **anchor** sentence, a **positive** sentence that is semantically similar, and a **negative** sentence that is semantically dissimilar. The length of each sentence is captured in `anchor_len`, `positive_len`, and `negative_len`, and the `source` column identifies the origin of the triplet, providing additional context for the data.
+
+## Use Cases
+
+This dataset is ideal for:
+
+- Training embeddings for semantic search systems.
+- Fine-tuning language models on Arabic textual similarities.
+- Evaluating embedding-based retrieval models, particularly in triplet-based tasks.
+
+The dataset spans different domains, such as general knowledge (WikiMatrix), public speaking (TedTalks), and QA forums (ArabicQuoraDuplicates), ensuring a diverse understanding of Arabic language semantics.
+