{"id":13723231,"url":"https://github.com/sinaahmadi/klpt","last_synced_at":"2025-05-07T16:32:35.403Z","repository":{"id":45074736,"uuid":"310766025","full_name":"sinaahmadi/klpt","owner":"sinaahmadi","description":"The Kurdish Language Processing Toolkit","archived":false,"fork":false,"pushed_at":"2024-09-18T14:53:14.000Z","size":5893,"stargazers_count":93,"open_issues_count":5,"forks_count":14,"subscribers_count":9,"default_branch":"master","last_synced_at":"2024-11-08T15:50:49.074Z","etag":null,"topics":["kurdish","kurdish-language-processing","kurdish-oss","kurdish-stemming","kurdish-tokenization","language-technology","less-resource-languages","natural-language-processing","toolkit"],"latest_commit_sha":null,"homepage":"https://sinaahmadi.github.io/klpt/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/sinaahmadi.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":".github/FUNDING.yml","license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null},"funding":{"github":"sinaahmadi","patreon":null,"open_collective":null,"ko_fi":"sinaahmadi","tidelift":null,"community_bridge":null,"liberapay":null,"issuehunt":null,"otechie":null,"custom":null}},"created_at":"2020-11-07T04:22:26.000Z","updated_at":"2024-10-15T19:29:07.000Z","dependencies_parsed_at":"2022-08-26T10:00:28.998Z","dependency_job_id":null,"html_url":"https://github.com/sinaahmadi/klpt","commit_stats":null,"previous_names":[],"tags_count":4,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sinaahmadi%2Fklpt","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sinaahmadi%2Fklpt/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sinaahmadi%2Fklpt/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sinaahmadi%2Fklpt/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sinaahmadi","download_url":"https://codeload.github.com/sinaahmadi/klpt/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":224621141,"owners_count":17342105,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["kurdish","kurdish-language-processing","kurdish-oss","kurdish-stemming","kurdish-tokenization","language-technology","less-resource-languages","natural-language-processing","toolkit"],"created_at":"2024-08-03T01:01:37.512Z","updated_at":"2024-11-14T12:31:44.034Z","avatar_url":"https://github.com/sinaahmadi.png","language":"Python","funding_links":["https://github.com/sponsors/sinaahmadi","https://ko-fi.com/sinaahmadi"],"categories":["Development","Natural Language Processing"],"sub_categories":["Tools","Libraries and Tools"],"readme":"# Kurdish Language Processing Toolkit\n\n\u003cp align=\"center\" width=\"100%\"\u003e\n    \u003cimg width=\"33%\" src=\"https://raw.githubusercontent.com/sinaahmadi/klpt/master/docs/img/KLPT_logo.png\"\u003e \n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n    \u003ca href=\"\"\u003e\n        \u003cimg alt=\"Build\" src=\"https://badges.frapsoft.com/os/v1/open-source.png?v=103\"\u003e\n    \u003c/a\u003e\n    \u003ca href=\"https://github.com/sinaahmadi/KLPT/blob/master/license\"\u003e\n        \u003cimg alt=\"GitHub\" src=\"https://img.shields.io/badge/license-CC%20BY--SA%204.0-blue\"\u003e\n    \u003c/a\u003e\n    \u003ca href=\"\"\u003e\n        \u003cimg alt=\"PyPI - Downloads\" src=\"https://img.shields.io/pypi/dm/klpt\"\u003e\n    \u003c/a\u003e\n    \u003ca href=\"https://sinaahmadi.github.io/klpt/\"\u003e\n        \u003cimg alt=\"Documentation\" src=\"https://img.shields.io/website?down_color=green\u0026down_message=online\u0026up_color=orange\u0026url=https%3A%2F%2Fsinaahmadi.github.io%2FKLPT%2F\"\u003e\n    \u003c/a\u003e\n    \u003ca href=\"https://gitter.im/KurdishNLP/community?utm_source=badge\u0026utm_medium=badge\u0026utm_campaign=pr-badge\"\u003e\n      \u003cimg alt=\"Documentation\" src=\"https://badges.gitter.im/KurdishNLP/community.svg\"\u003e\n    \u003c/a\u003e\n    \u003ca href=\"https://badge.fury.io/py/klpt\"\u003e\n        \u003cimg src=\"https://badge.fury.io/py/klpt.svg\" alt=\"PyPI version\" height=\"18\"\u003e\n    \u003c/a\u003e\n\u003c/p\u003e\n\n\n### Welcome / *Hûn bi xêr hatin* / بە خێر بێن! 🙂\n\nKurdish Language Processing Toolkit--KLPT is a [natural language processing](https://en.wikipedia.org/wiki/Natural_language_processing) (NLP) toolkit in Python for the [Kurdish language](https://en.wikipedia.org/wiki/Kurdish_languages). The current version comes with four core modules, namely `preprocess`, `stem`, `transliterate` and `tokenize` and addresses basic language processing tasks such as text preprocessing, stemming, tokenization, spell-checking and morphological analysis for the [Sorani](https://en.wikipedia.org/wiki/Sorani) and the [Kurmanji](https://en.wikipedia.org/wiki/Kurmanji) dialects of Kurdish.\n\n---\n#### Latest update on April 29th, 2022 🎉\n\nIn the latest version, I focused on Kurmanji for which a morphological analyzer, a stemmer and a lemmatizer are now added to the toolkit. These tasks were partially addressed previously using the [Apertium project](https://github.com/apertium/apertium-kmr). Now, that is fully replaced by the Kurmanji implementation of [Kurdish Hunspell](https://github.com/sinaahmadi/KurdishHunspell). \n\n---\n\n## Install KLPT\n\n\u003c!--For detailed installation instructions, see the [documentation]().--\u003e\n\n- **Operating system**: macOS / OS X · Linux · Windows (Cygwin, MinGW, Visual\n  Studio)\n- **Python version**: Python 3.5+ \n- **Package managers**: [pip](https://pypi.org/project/klpt/)\n\n[pip]: https://pypi.org/project/spacy/\n[conda]: https://anaconda.org/conda-forge/spacy\n\n### pip\n\nUsing pip, KLPT releases are available as source packages and binary wheels. Please make sure that a compatible Python version is installed:\n\n```bash\npip install klpt\n```\n\nAll the data files including lexicons and morphological rules are also installed with the package. \n\nAlthough KLPT is not dependent on any NLP toolkit, there is one important requirement, particularly for the `stem` module. That is [`cyhunspell`](https://pypi.org/project/cyhunspell/) which should be installed with a version \u003e= 2.0.1.\n\n### About this version\n\nPlease note that KLPT is under development and some of the functionalities will appear in the future versions. You can find out regarding the progress of each task at the [Projects](https://github.com/sinaahmadi/KLPT/projects) section. In the current version, the following tasks are included:\n\n\u003ctable\u003e\n\u003cthead\u003e\n  \u003ctr\u003e\n    \u003cth\u003eModules\u003cbr\u003e\u003c/th\u003e\n    \u003cth\u003eTasks\u003c/th\u003e\n    \u003cth\u003eSorani (ckb)\u003c/th\u003e\n    \u003cth\u003eKurmanji (kmr)\u003c/th\u003e\n  \u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n  \u003ctr\u003e\n    \u003ctd rowspan=\"4\"\u003e\u003ccode\u003epreprocess\u003c/code\u003e\u003c/td\u003e\n    \u003ctd\u003enormalization\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v0.1.0)\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v0.1.0)\u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd\u003estandardization\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v0.1.0)\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v0.1.0)\u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd\u003eunification of numerals\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v0.1.0)\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v0.1.0)\u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd\u003estopwords\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v0.1.4)\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v0.1.4)\u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd rowspan=\"4\"\u003e\u003ccode\u003etokenize\u003c/code\u003e\u003c/td\u003e\n    \u003ctd\u003eword tokenization\u003cbr\u003e\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v0.1.0)\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v0.1.0)\u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd\u003eMWE tokenization\u003cbr\u003e\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v0.1.0)\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v0.1.0)\u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd\u003esentence tokenization\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v0.1.0)\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v0.1.0)\u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd\u003epart-of-speech tagging\u003c/td\u003e\n    \u003ctd\u003e\u0026#x2717;\u003c/td\u003e\n    \u003ctd\u003e\u0026#x2717;\u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd rowspan=\"4\"\u003e\u003ccode\u003etransliterate\u003c/code\u003e\u003c/td\u003e\n    \u003ctd\u003eArabic to Latin\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v0.1.0)\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v0.1.0)\u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd\u003eLatin to Arabic\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v0.1.0)\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v0.1.0)\u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd\u003eDetection of u/w and î/y\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v0.1.0)\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v0.1.0)\u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd\u003eDetection of Bizroke ( \u003ci\u003ei\u003c/i\u003e )\u003c/td\u003e\n    \u003ctd\u003e\u0026#x2717;\u003c/td\u003e\n    \u003ctd\u003e\u0026#x2717;\u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd rowspan=\"5\"\u003e\u003ccode\u003estem\u003c/code\u003e\u003c/td\u003e\n    \u003ctd\u003emorphological analysis\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v0.1.0)\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v0.1.1)\u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd\u003estemming\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v.0.1.5)\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v.0.1.6) 🆕\u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd\u003elemmatization\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v.0.1.5)\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v.0.1.6) 🆕\u003c/td\u003e\n  \u003c/tr\u003e\n  \u003ctr\u003e\n    \u003ctd\u003espell error detection and correction\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v0.1.0)\u003c/td\u003e\n    \u003ctd\u003e\u0026#10003; (v.0.1.6) 🆕\u003c/td\u003e\n  \u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\n\n## Basic usage\n\nOnce the package is installed, you can import the toolkit as follows:\n\n```python\nimport klpt\n```\n\nIn the following, a few examples are provided to work with various modules. Almost all the classes have three arguments in common:\n\n- `dialect`: the name of the dialect as `Sorani` or `Kurmanji` (ISO 639-3 code will be also added)\n- `script`: the script of your input text as \"Arabic\" or \"Latin\"\n- `numeral`: the type of the numerals as\n\t- Arabic [١٢٣٤٥٦٧٨٩٠]\n\t- Farsi [۱۲۳۴۵۶۷۸۹۰]\n\t- Latin [1234567890]\n\n### Preprocess\n\nThis module deals with normalizing scripts and orthographies by using writing conventions based on dialects and scripts. The goal is not to correct the orthography but to normalize the text in terms of the encoding and common writing rules. The input encoding should be in UTF-8 only. To this end, three functions are provided as follows:\n\n- `normalize`: deals with different encodings and unifies characters based on dialects and scripts\n- `standardize`: given a normalized text, it returns standardized text based on the Kurdish orthographies following recommendations for [Kurmanji](https://books.google.ie/books?id=Z7lDnwEACAAJ) and [Sorani](http://yageyziman.com/Renusi_Kurdi.htm)\n- `unify_numerals`: conversion of the various types of numerals used in Kurdish texts\n- `preprocess`: one single function for normalization, standardization and unification of numerals\n\nIt is recommended that the output of this module be used as the input of subsequent tasks in an NLP pipeline.\n\n```python\n\u003e\u003e\u003e from klpt.preprocess import Preprocess\n\n\u003e\u003e\u003e preprocessor_ckb = Preprocess(\"Sorani\", \"Arabic\", numeral=\"Latin\")\n\u003e\u003e\u003e preprocessor_ckb.normalize(\"لە ســـاڵەکانی ١٩٥٠دا\")\n'لە ساڵەکانی 1950دا'\n\u003e\u003e\u003e preprocessor_ckb.standardize(\"راستە لەو ووڵاتەدا\")\n'ڕاستە لەو وڵاتەدا'\n\u003e\u003e\u003e preprocessor_ckb.unify_numerals(\"٢٠٢٠\")\n'2020'\n\u003e\u003e\u003e preprocessor_ckb.preprocess(\"راستە لە ووڵاتەی ٢٣هەمدا\")\n'ڕاستە لە وڵاتەی 23هەمدا'\n\n\u003e\u003e\u003e preprocessor_kmr = Preprocess(\"Kurmanji\", \"Latin\")\n\u003e\u003e\u003e preprocessor_kmr.standardize(\"di sala 2018-an\")\n'di sala 2018an'\n\u003e\u003e\u003e preprocessor_kmr.standardize(\"hêviya\")\n'hêvîya'\n```\n\nIn addition, it is possible to remove Kurdish [stopwords](https://en.wikipedia.org/wiki/Stop_word) using the `stopwords` variable. You can define a function like the following to do so:\n\n```python\nfrom klpt.preprocess import Preprocess\n\ndef remove_stopwords(text, dialect, script):\n    p = Preprocess(dialect, script)\n    return [token for token in text.split() if token not in p.stopwords]\n```\n\n### Tokenization\n\nThis module focuses on the tokenization of both Kurmanji and Sorani dialects of Kurdish with the following functions:\n\n- `word_tokenize`: tokenization of texts into tokens (both [multi-word expressions](https://aclweb.org/aclwiki/Multiword_Expressions) and single-word tokens).\n- `mwe_tokenize`: tokenization of texts by only taking compound forms into account\n- `sent_tokenize`: tokenization of texts into sentences\n\nThis module is based on the [Kurdish tokenization project](https://github.com/sinaahmadi/KurdishTokenization). It is recommended that the output of this module be used as the input of the `Stem` module. \n\n```python\n\u003e\u003e\u003e from klpt.tokenize import Tokenize\n\n\u003e\u003e\u003e tokenizer = Tokenize(\"Kurmanji\", \"Latin\")\n\u003e\u003e\u003e tokenizer.word_tokenize(\"ji bo fortê xwe avêtin\")\n['▁ji▁', 'bo', '▁▁fortê‒xwe‒avêtin▁▁']\n\u003e\u003e\u003e tokenizer.mwe_tokenize(\"bi serokê hukûmeta herêma Kurdistanê Prof. Salih re saz kir.\")\n'bi serokê hukûmeta herêma Kurdistanê Prof . Salih re saz kir .'\n\n\u003e\u003e\u003e tokenizer_ckb = Tokenize(\"Sorani\", \"Arabic\")\n\u003e\u003e\u003e tokenizer_ckb.word_tokenize(\"بە هەموو هەمووانەوە ڕێک کەوتن\")\n['▁بە▁', '▁هەموو▁', 'هەمووانەوە', '▁▁ڕێک‒کەوتن▁▁']\n```\n\n### Transliteration\n\nThis module aims at transliterating one script of Kurdish into another one. Currently, only the Latin-based and the Arabic-based scripts of Sorani and Kurmanji are supported. The main function in this module is `transliterate()` which also takes care of detecting the correct form of double-usage graphemes, namely و ↔ w/u and ی ↔ î/y. In some specific occasions, it can also predict the placement of the missing *i* (also known as *Bizroke/بزرۆکە*).\n\nThe module is based on the [Kurdish transliteration project](https://github.com/sinaahmadi/wergor).\n\n```python\n\u003e\u003e\u003e from klpt.transliterate import Transliterate\n\u003e\u003e\u003e transliterate = Transliterate(\"Kurmanji\", \"Latin\", target_script=\"Arabic\")\n\u003e\u003e\u003e transliterate.transliterate(\"rojhilata navîn\")\n'رۆژهلاتا ناڤین'\n\n\u003e\u003e\u003e transliterate_ckb = Transliterate(\"Sorani\", \"Arabic\", target_script=\"Latin\")\n\u003e\u003e\u003e transliterate_ckb.transliterate(\"لە وڵاتەکانی دیکەدا\")\n'le wiłatekanî dîkeda'\n```\n\n### Stem\n\nThe Stem module deals with various tasks, mainly through the following functions:\n- `check_spelling`: spell error detection\n- `correct_spelling`: spell error correction\n- `analyze`: morphological analysis\n- `stem`: stemming, e.g. \"بڕ\" → \"بڕاوە\" or \"dixwî\" → \"xw\"\n- `lemmatize`: lemmatization, e.g. \"بردن\" → \"بردمنەوە\" or \"jimartibûye\" → \"hejmartin\"\n\nThe module is based on the [Kurdish Hunspell project](https://github.com/sinaahmadi/KurdishHunspell) for Sorani and the [Apertium project](https://github.com/apertium/apertium-kmr) for Kurmanji. Please note that this module is currently getting further completed and we are aware of its current shortcomings.\n\n```python\n\u003e\u003e\u003e from klpt.stem import Stem\n\u003e\u003e\u003e stemmer = Stem(\"Sorani\", \"Arabic\")\n\u003e\u003e\u003e stemmer.check_spelling(\"سوتاندبووت\")\nFalse\n\u003e\u003e\u003e stemmer.correct_spelling(\"سوتاندبووت\")\n(False, ['ستاندبووت', 'سووتاندبووت', 'سووڕاندبووت', 'ڕووتاندبووت', 'فەوتاندبووت', 'بووژاندبووت'])\n\u003e\u003e\u003e stemmer.analyze(\"دیتبامن\")\n[{'pos': ['verb'], 'description': 'past_stem_transitive_active', 'stem': 'دی', 'lemma': ['دیتن'], 'base': 'دیت', 'prefixes': '', 'suffixes': 'بامن'}]\n\u003e\u003e\u003e stemmer.stem(\"دەچینەوە\")\n['چ']\n\u003e\u003e\u003e stemmer.stem(\"گورەکە\", mark_unknown=True) # گوڵەکە in Hewlêrî dialect\n['_گور_']\n\u003e\u003e\u003e stemmer.lemmatize(\"گوڵەکانم\")\n['گوڵ', 'گوڵە']\n\n\u003e\u003e\u003e stemmer = Stem(\"Kurmanji\", \"Latin\")\n\u003e\u003e\u003e stemmer.analyze(\"dibêjim\")\n[{'base': 'bêj', 'prefixes': 'di', 'suffixes': 'im', 'pos': ['verb'], 'description': 'present_stem_transitive_active', 'stem': 'bêj', 'lemma': ['gotin']}]\n\u003e\u003e\u003e stemmer.stem(\"dixwî\")\n['xw']\n\u003e\u003e\u003e stemmer.lemmatize(\"jimartibûye\")\n['hejmartin']\n```\n\n📖 **Please note that a more complete documentation of the toolkit is available at [https://sinaahmadi.github.io/klpt/](https://sinaahmadi.github.io/klpt/)**.\n\n## Become a sponsor \n\nPlease consider donating to the project. Data annotation and resource creation requires tremendous amount of time and linguistic expertise. Even a trivial donation will make a difference. You can do so by [becoming a sponsor](https://github.com/sponsors/sinaahmadi) to accompany me in this journey and help the Kurdish language have a better place within other natural languages on the Web. Depending on your support,\n\n- You can be an official sponsor\n- You will get a GitHub sponsor badge on your profile\n- If you have any questions, I will focus on it\n- If you want, I will add your name or company logo on the front page of your preferred project\n- Your contribution will be acknowledged in one of my future papers in a field of your choice\n\n*And, thanks for those who have already sponsored this project. More significant achievements will be made thanks to you!*\n\n## Contribute\n\nAre you interested in this project? Each task is addressed individually. Please check the following repositories to find which one you are more interested in:\n\n- [Kurdish tokenization](https://github.com/sinaahmadi/KurdishTokenization)\n- [Kurdish Hunspell](https://github.com/sinaahmadi/KurdishHunspell)\n- [Kurdish transliteration](https://github.com/sinaahmadi/wergor)\n\nIn addition, our main objective is to extend the current toolkit to include more tasks, particularly part-of-speech tagging, named-entity recognition and syntactic analysis. Further instructions are provided at [https://sinaahmadi.github.io/klpt/about/contributing/](https://sinaahmadi.github.io/klpt/about/contributing/). You can also join us on [Gitter](https://gitter.im/KurdishNLP/community).\n\nDon't forget, **open-source is fun!** 😊\n\n## Requirements\n- Python \u003e=3.6\n- [`cyhunspell`](https://pypi.org/project/cyhunspell/) \u003e= 2.0.1\n\n## Cite this project\nPlease consider citing [this paper](https://sinaahmadi.github.io/docs/articles/ahmadi2020klpt.pdf), if you use any part of the data or the tool ([`bib` file](https://sinaahmadi.github.io/bibliography/ahmadi2020klpt.txt)):\n\n\t@inproceedings{ahmadi2020klpt,\n\t    title = \"{KLPT--Kurdish Language Processing Toolkit}\",\n\t    author = \"Ahmadi, Sina\",\n\t    booktitle = \"Proceedings of the second Workshop for {NLP} Open Source Software ({NLP}-{OSS})\",\n\t    month = nov,\n\t    year = \"2020\",\n\t    publisher = \"Association for Computational Linguistics\"\n\t}\n\n\n## License \n\u003ca rel=\"license\" href=\"http://creativecommons.org/licenses/by-sa/4.0/\"\u003e\u003cimg alt=\"Creative Commons License\" style=\"border-width:0\" src=\"https://i.creativecommons.org/l/by-sa/4.0/88x31.png\" /\u003e\u003c/a\u003e\u003cbr /\u003e\u003cspan xmlns:dct=\"http://purl.org/dc/terms/\" property=\"dct:title\"\u003eKurdish Language Processing Toolkit\u003c/span\u003e by \u003ca xmlns:cc=\"http://creativecommons.org/ns#\" href=\"https://github.com/sinaahmadi/klpt\" property=\"cc:attributionName\" rel=\"cc:attributionURL\"\u003eSina Ahmadi\u003c/a\u003e is licensed under a \u003ca rel=\"license\" href=\"http://creativecommons.org/licenses/by-sa/4.0/\"\u003eCreative Commons Attribution-ShareAlike 4.0 International License\u003c/a\u003e which means:\n\n- **You are free to share**, copy and redistribute the material in any medium or format and also adapt, remix, transform, and build upon the material\nfor any purpose, **even commercially**. \n- **You must give appropriate credit**, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.\n- If you remix, transform, or build upon the material, **you must distribute your contributions under the same license as the original**.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsinaahmadi%2Fklpt","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsinaahmadi%2Fklpt","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsinaahmadi%2Fklpt/lists"}