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Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
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Noor-Sharaye v.1. A Benchmark Dataset of Complex Words for Evaluating Arabic Analyzers

Authors: Minaei-Bidgoli, Behrouz;

Noor-Sharaye v.1. A Benchmark Dataset of Complex Words for Evaluating Arabic Analyzers

Abstract

The Noor-Sharaye dataset is a morphologically annotated Classical Arabic corpus containing approximately 205,000 word instances extracted from 17 different Classical Arabic books, including Quranic, Fiqh, Hadith, and historical texts. Each token is enriched with detailed linguistic annotations such as Stem Lemma Root part-of-speech tags (pos) Segmentation Grammatical case Gender, Number Affix-level features The data are encoded in UTF-8 CSV, XML, and JSON formats for broad compatibility. This resource supports stemming, root extraction, morphological analysis, and benchmarking of AI-based models in Arabic Natural Language Processing

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average