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--- |
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language: |
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- ku |
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- ckb |
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- kmr |
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- hac |
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size_categories: |
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- 1B<n<10B |
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license: cc-by-4.0 |
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pretty_name: KurCorpus 2B |
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tags: |
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- kurdish |
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- low-resource |
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- language-modeling |
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--- |
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# KurCorpus 2B |
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-informational) |
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[](https://doi.org/10.17632/fb5xhhn6m5.1) |
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**KurCorpus 2B** is a multidialectal Kurdish text corpus (>2B tokens) for large-scale language modeling and downstream NLP. |
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- **Dialects:** Sorani (ckb), Kurmanji/Badini (kmr), Hawrami/Gorani (hac) |
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- **License:** CC BY 4.0 |
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- **Repo:** https://huggingface.co/datasets/abdulhade/Kurdishcorpus |
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- **External record:** Mendeley Data DOI `10.17632/fb5xhhn6m5.1` |
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--- |
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## TL;DR |
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- Ready for **pretraining** and **finetuning** Kurdish LMs |
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- Single field **`text`** (UTF-8), offered as large archives or sharded `.txt(.gz)` |
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- Includes **normalization and cleaning** (Unicode, orthography, noise removal with placeholders like `[URL]`, `[EMAIL]`) |
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- No official splits; create your own task-specific splits and report dialect coverage |
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--- |
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## Quickstart |
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```python |
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from datasets import load_dataset |
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# Stream without downloading everything at once (recommended for very large corpora) |
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ds = load_dataset("abdulhade/Kurdishcorpus", split="train", streaming=True) |
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for i, ex in enumerate(ds.take(5)): |
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print(ex["text"]) |
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``` |
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# Text Normalization (AsoSoft Library) |
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This repository documents how Central Kurdish text is normalized with the **AsoSoft Library** before release. The goal is to standardize Unicode, punctuation, numerals, and common web artifacts so downstream tokenizers and language models see clean, consistent text. |
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- Library: **AsoSoft Library** (C#/.NET) by Aso Mahmudi |
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- Repo: https://github.com/AsoSoft/AsoSoft-Library |
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- Scope: Kurdish Sorani (ckb) primary, with script-agnostic steps for other Kurdish varieties (kmr, hac) |
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--- |
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## Why normalize |
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- Reduce spurious vocabulary caused by look-alike glyphs and legacy encodings. |
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- Ensure consistent numerals and punctuation for stable tokenization. |
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- Replace privacy-sensitive artifacts like URLs and emails with safe placeholders. |
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- Remove invisible noise (tatweel, zero-widths, control chars) that hurts training. |
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--- |
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## What the pipeline does |
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### 1) Legacy encodings to Unicode (conditional) |
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Applied only when legacy font artifacts are detected. |
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- `AliK2Unicode` |
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- `AliWeb2Unicode` |
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- `Dylan2Unicode` |
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- `Zarnegar2Unicode` |
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### 2) HTML and web artifacts |
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- `ReplaceHtmlEntity` converts entities (e.g. `"` → `"`). |
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- `ReplaceUrlEmail` replaces URLs and emails with `[URL]` and `[EMAIL]`. |
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### 3) Unicode standardization and Kurdish-specific fixes |
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`Normalize(...)` with deep and additional corrections enabled. |
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- Replace Arabic Presentation Forms with standard code points. |
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- Remove Tatweel U+0640 and stray control/zero-width characters. |
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- Normalize dashes and spaces. |
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- Map visually similar Arabic letters to Kurdish standard forms (e.g. ڪ, ے, ٶ → ک, ی, ؤ). |
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- Kurdish-specific standardization of `ە, هـ, ی, ک`. |
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- Correct frequent mis-conversions from non-Unicode fonts. |
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- Optionally convert word-initial `ر` to `ڕ`. |
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### 4) Punctuation and whitespace |
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- `NormalizePunctuations(text, separateAllPunctuations=false)` ensures no extra spaces around punctuation. |
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- `TrimLine` trims leading/trailing whitespace including zero-width spaces. |
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### 5) Numerals and digit separation |
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- `UnifyNumerals(text, "en")` normalizes all digits to ASCII 0–9 for tokenizer stability. |
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- `SeperateDigits` inserts spaces between digits and adjacent letters (e.g. `12کەس` → `12 کەس`). |
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> Note: For kmr/hac lines, we only apply script-agnostic steps (HTML/entity cleanup, URL/email replacement, Unicode cleanup, punctuation, numerals, trimming). We do not transliterate or run G2P on released text. |
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--- |
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## Reproducible configuration |
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We run the following configuration in order. The last step that applies is the one whose conditions are met. |
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```csharp |
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using AsoSoftLibrary; |
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string NormalizeCkbLine(string text) |
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{ |
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// 1) Legacy converters (conditional, heuristic triggers) |
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if (LooksLikeAliK(text)) text = AsoSoft.AliK2Unicode(text); |
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if (LooksLikeAliWeb(text)) text = AsoSoft.AliWeb2Unicode(text); |
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if (LooksLikeDylan(text)) text = AsoSoft.Dylan2Unicode(text); |
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if (LooksLikeZarnegar(text)) text = AsoSoft.Zarnegar2Unicode(text); |
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// 2) HTML and web artifacts |
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text = AsoSoft.ReplaceHtmlEntity(text); |
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text = AsoSoft.ReplaceUrlEmail(text); // replaces with [URL], [EMAIL] |
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// 3) Unicode standardization (+ Kurdish fixes) |
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// changeInitialR=true enables initial ر → ڕ |
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text = AsoSoft.Normalize( |
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text: text, |
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isOnlyKurdish: true, |
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changeInitialR: true, |
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deepUnicodeCorrectios: true, |
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additionalUnicodeCorrections: true, |
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usersReplaceList: null |
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); |
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// 4) Punctuation and whitespace |
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text = AsoSoft.NormalizePunctuations(text, separateAllPunctuations: false); |
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text = AsoSoft.TrimLine(text); |
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// 5) Numerals and digit separation |
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text = AsoSoft.UnifyNumerals(text, "en"); |
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text = AsoSoft.SeperateDigits(text); |
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return text; |
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} |
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``` |
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Heuristic detectors like `LooksLikeAliK` check for characteristic code points and glyph ranges associated with each legacy font family. The converters are applied only when such patterns are present. |
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--- |
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## Before and after examples |
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``` |
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Input : دەقی«کوردی » و ڕێنووس ،((خاڵبەندی )) چۆنە ؟ |
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Output: دەقی «کوردی» و ڕێنووس، «خاڵبەندی» چۆنە? |
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``` |
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``` |
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Input : ژمارەکانی ٤٥٦ و ۴۵۶ و 456 |
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Output: ژمارەکانی 456 و 456 و 456 |
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``` |
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``` |
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Input : دەقے شیَعري خـــۆش. رهنگهكاني خاك |
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Output: دەقی شێعری خۆش. ڕەنگەکانی خاک |
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``` |
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``` |
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Input : ئێوە "دەق" لە زمانی <کوردی> دەنووسن |
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Output: ئێوە "دەق" بە زمانی <کوردی> دەنووسن |
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``` |
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``` |
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Input : لە ساڵی1950دا1000دۆلاریان بە 5کەس دا |
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Output: لە ساڵی 1950 دا 1000 دۆلاریان بە 5 کەس دا |
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``` |
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--- |
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## What we do not do |
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- No transliteration or G2P on the released corpus. The text remains in its native script. |
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- No poem meter classification during release processing. |
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- No semantic rewriting beyond canonical character and punctuation normalization. |
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--- |
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## Dialect coverage policy |
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- **ckb**: full AsoSoft normalization including Kurdish-specific fixes. |
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- **kmr/hac**: script-agnostic cleanup only. We avoid ckb-specific letter substitutions to preserve dialectal orthography and phonology. |
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--- |
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## Quality checks |
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- Character inventory auditing before and after normalization. |
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- Proportion of placeholders `[URL]`, `[EMAIL]` to detect crawler bias. |
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- Count of removed control and zero-width characters. |
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- Round-trip sampling with spot manual verification on ambiguous lines. |
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- Determinism check: same input produces same output across runs. |
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--- |
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## Reproducing locally |
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1. Install .NET 6 or newer. |
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2. Add AsoSoft Library via NuGet in your C# project. |
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3. Pipe your text through a console app using the configuration above. |
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Example console usage: |
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```bash |
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dotnet run --project NormalizerApp --input data/raw.txt --output data/normalized.txt |
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``` |
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Where `NormalizerApp` calls `NormalizeCkbLine` for each line. |
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--- |
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## Parameters you can tune |
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- `changeInitialR`: set to `false` if you do not want `ر` to become `ڕ` word-initially. |
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- `UnifyNumerals` target: `"en"` for ASCII 0–9 or `"ar"` for Arabic-Indic digits, depending on your tokenizer. |
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- `separateAllPunctuations`: set to `true` if you prefer all punctuation to be isolated by spaces for whitespace-tokenized pipelines. |
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--- |
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## Cite |
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If you use **KurCorpus 2B**, please cite: |
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[](https://doi.org/10.17632/fb5xhhn6m5.1) |
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**BibTeX** |
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```bibtex |
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@dataset{rawf2025kurcorpus2b, |
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title = {KurCorpus 2B: A Multidialectal 2-Billion-Token Corpus for Kurdish Language Modeling}, |
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author = {Rawf, Karwan Mahdi and Abdullah, Abdullah and Hussein, Amanj and Mohammed, Haukar}, |
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year = {2025}, |
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version = {1}, |
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howpublished = {Mendeley Data}, |
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doi = {10.17632/fb5xhhn6m5.1} |
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} |
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