NHLOCAL/judaic-texts-structure

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license: mit task_categories: - other language: - he tags: - hebrew - judaism - jewish-studies - structured-data - talmud - tanakh - halakha - rambam - mishna pretty_name: "Jewish Texts Structure Dataset" size_categories: - 10K<n<100K

Jewish Texts Structure Dataset

Summary

This dataset provides a structured, machine-readable catalog of the divisions (chapters, pages, sections, etc.) of fundamental Jewish texts. It is designed to be a foundational resource for developers and researchers building applications, tools, or conducting analyses related to Jewish studies.

The dataset contains 14,470 records, with each record representing a single unit of study (e.g., one chapter of Tanakh, one page-side (Amud) of Talmud, or one Siman in Shulchan Aruch).

The following corpora are included:

• Tanakh (תנ"ך): The Hebrew Bible, divided by Perek (chapter).
• Mishna (משנה): The six orders of the Mishna, divided by Perek (chapter).
• Talmud Bavli (תלמוד בבלי): The Babylonian Talmud, divided by Daf (folio) and Amud (page-side).
• Talmud Yerushalmi (תלמוד ירושלמי): The Jerusalem Talmud, divided by Daf (folio) and Amud (page-side).
• Rambam (רמב"ם): Maimonides' Mishneh Torah, divided by Sefer (book), Hilkhot (laws), and Perek (chapter).
• Halakha (הלכה): Major Halakhic codes, including:
  • Arba'ah Turim (ארבע טורים)
  • Shulchan Aruch (שולחן ערוך)
  • Mishnah Berurah (משנה ברורה)
  • Biur Halakha (ביאור הלכה)

Potential Use Cases

This dataset is not intended for training a model directly but serves as a structured knowledge base. Potential applications include:

• Study Trackers: Powering applications for tracking daily study cycles like Daf Yomi, Mishnah Yomit, or Rambam Yomi.
• API Development: Creating a REST API to query the structure of Jewish texts (e.g., GET /api/shas/berakhot to retrieve all pages of the tractate).
• Data Visualization: Generating visualizations to compare the lengths and structures of different books and sections.
• Educational Tools: Building backends for educational software that navigate or reference these texts.
• Linking to Content: Serving as a foundational index to link to full-text content from sources like Sefaria or Wikisource.

Languages

The data itself is structural, but all names for categories, books, and units are in Hebrew (he).

Dataset Structure

Data Instances

Each record is a dictionary representing a single, learnable unit.

Example from שולחן ערוך אורח חיים (a simple structure):

{
  "category": "הלכה",
  "subcategory": "שולחן ערוך",
  "book": "שולחן ערוך אורח חיים",
  "part_name": null,
  "unit_type": "סימן",
  "unit_number": 25,
  "unit_name": "סימן כ\"ה"
}

Example from תלמוד בבלי (using part_name for Amud):

{
  "category": "תלמוד בבלי",
  "subcategory": "סדר מועד",
  "book": "שבת",
  "part_name": "עמוד א",
  "unit_type": "דף",
  "unit_number": 2,
  "unit_name": "דף ב' עמוד א"
}

Example from רמב"ם (using part_name for Hilkhot): This shows how a single book (ספר המדע) is broken down into parts (הלכות דעות).

{
  "category": "רמב\"ם",
  "subcategory": "משנה תורה",
  "book": "ספר המדע",
  "part_name": "הלכות דעות",
  "unit_type": "פרק",
  "unit_number": 1,
  "unit_name": "פרק א'"
}

Data Fields

• category (string): The highest-level collection, defined by the name at the root of the source JSON file. e.g., "הלכה", "רמב"ם".
• subcategory (string): A major section within a category, from the name field of a subcategories object. e.g., "שולחן ערוך", "משנה תורה", "סדר מועד".
• book (string): The name of the specific book, tractate, or section. This is typically a key in the books object in the source JSON. e.g., "בראשית", "שולחן ערוך חושן משפט", "ספר המדע", "ביאור הלכה".
• part_name (string | null): An optional field for subdivisions within a book. This is used for different purposes depending on the text:
  • In the Talmud, it's עמוד א or עמוד ב.
  • In the Rambam, it's the name of the laws (הלכות), e.g., "הלכות דעות".
  • In Mishnah Berurah and Biur Halakha, it's the volume number, e.g., "חלק א'".
  • It is null if the book is not subdivided in this way (e.g., most of Shulchan Aruch).
• unit_type (string): The name of the unit of division, defined by content_type in the source JSON. e.g., "פרק", "דף", "סימן".
• unit_number (int): The integer value of the unit, e.g., 1 for פרק א', 120 for דף קכ.
• unit_name (string): A human-readable name for the unit, combining the type and its Hebrew numerical representation (Gematria), e.g., "פרק י'", "דף ב' עמוד א", "סימן תכ"ט".

Data Splits

The dataset consists of a single split: train.

Dataset Creation

Curation Rationale

The dataset was programmatically generated from a set of JSON configuration files that define the structure of each corpus. This approach was chosen to ensure consistency, accuracy, and easy maintainability. The source files are based on the canonical, standard print editions of these texts.

Source Data

The data was generated from a collection of hand-curated JSON files that describe the hierarchical structure of each text. The generation script parses these files according to their specific format:

• Simple Range: For texts like שולחן ערוך אורח חיים, the structure is defined by a simple "pages" count (e.g., { "pages": 697 }). The script generates units from 1 to this number.
• Range with Exclusions: For texts like טור יורה דעה, the structure includes a "pages" count and an "exclude" array (e.g., { "pages": 403, "exclude": [169] }). The script generates units from 1 to the page count, skipping any numbers present in the exclude list.
• Structured Parts: For complex texts like Rambam or Mishnah Berurah, the structure is defined by a "parts" array. Each object in the array specifies a name (which becomes the part_name in the output), a start unit, and an end unit.
• Structured Parts with Exclusions: For texts like Biur Halakha, the structure combines the parts array with an exclude list within each part, providing fine-grained control over which units are included.

This structured, declarative approach allows for a precise and verifiable representation of each text's canonical structure.

Annotations

The dataset is not annotated in a traditional sense. It is a structured representation of the canonical divisions of the texts. The generation process was fully automated based on the source JSON files.

Personal and Sensitive Information

This dataset contains no personal or sensitive information. It exclusively catalogs the structure of religious texts.

Additional Information

Dataset Curators

This dataset was curated and prepared by NHLOCAL.

Licensing Information

The dataset is released under the cc-by-4.0 License.

Citation Information

If you use this dataset in your work, please consider citing it as follows:

@dataset{nhlocal_judaic_texts_structure,
  author       = {NHLOCAL},
  title        = {judaic Texts Structure Dataset},
  year         = {2025},
  publisher    = {Hugging Face},
  version      = {1.1.0},
  url          = {https://huggingface.co/datasets/NHLOCAL/judaic-texts-structure}
}