Arabic Orthography and Hamza Writing Rules QA Dataset

#question answering #spelling rule identification #grammatical reasoning #Arabic orthography education #hamza spelling rules #Arabic spelling instruction

5000
0.3GB
JSON
CATL
MOBIUSI INC

Updated:2026-10-19

AI Analysis & Value Prop

Compiled from Arabic spelling instruction webpages, this dataset covers closed-domain questions on hamza position and seat letters, word joining and separation, final letters, ta marbuta, and spelling exceptions. Records provide normalized questions and answers, with rule categories, statements, analyses, and examples where available, supporting Arabic writing-rule retrieval, domain fine-tuning, and QA evaluation.

Dataset Insights

Sample Examples

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Technical Specifications

Field	Type	Description
file_name	string	File name
answer	string	A direct answer based on the original webpage content, including the relevant rule decision and explanation.
examples	array	Arabic words, letter forms, or spelling examples used to explain the rule, with accompanying explanations.
keywords	array	Arabic orthography keywords extracted from the question and answer for retrieval or categorization.
question	string	A clear, closed-domain question about Arabic orthography, derived from the original QA content.
has_exception	boolean	Indicates whether the QA content involves a spelling exception or special convention.
rule_category	string	The main Arabic orthography rule category addressed by the QA record.
source_record	object	The original question-and-answer content collected from a spelling instruction webpage, together with source page information.
hamza_analysis	object	A structured explanation of hamza position, seat letter, and decision criteria when relevant; may be empty when the question does not concern hamza.
rule_statement	string	A concise statement of the core spelling convention, suitable for rule-based decisions.
exception_notes	string	Notes on exceptions, special word forms, traditional spellings, or cases where a rule should not be generalized.

Compliance Statement

Authorization Type	Proprietary - Commercial AI Training License (No Redistribution)
Commercial Use	Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization	No PII, no real company names, simulated scenarios follow industry standards
Compliance System	Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

What topics does the dataset cover?: It is based on Arabic spelling instruction webpages and covers hamza position and seat letters, word joining and separation, final letters, ta marbuta, and spelling exceptions. Records include normalized questions and answers with related rule information.

How are the records structured?: Records include source webpage QA information, normalized questions and answers, rule categories, and rule statements. Hamza analysis may be included when relevant, along with examples, exception notes, and retrieval keywords. Refer to the dataset schema for the exact fields.

Which training and evaluation tasks does it support?: It supports Arabic spelling QA, closed-domain QA training, domain-specific supervised fine-tuning, and evaluation of rule decisions and exception handling. For formal teaching or publication, verify specific conclusions against authoritative Arabic orthography references.

How can I access the data, and what are the licensing terms?: Refer to the product page for available access methods, file specifications, and licensing terms. Since the content is sourced from instructional webpages, confirm the product license and any source-related rights before use, redistribution, or commercial deployment.

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Cite this Work

@dataset{Mobiusi2026,
  title={Arabic Orthography and Hamza Writing Rules QA Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/64c6ac29953df9e4a10152a377ccdf5a},
  urldate={2026-10-15},
  keywords={Arabic orthography,hamza rules,Arabic spelling QA,Arabic spelling standards,ta marbuta,Arabic closed-domain QA,Arabic SFT dataset,Arabic language model},
  version={1.0}
}

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