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Awesome Persian NLP/IR, Tools And Resources

Awesome Persian NLP/IR, Tools And Resources
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This list is curation of the best, not of everything. Please participate in its development.Thanks to ACL WEB.

Contents

Tools

Part-of-Speech Tagger

  • farsiNLPTools – Open-source dependency parser, part-of-speech tagger, and text normalizer for Farsi (Persian).
  • HAZM – Python library for digesting Persian text.
  • Persian Language Model for HunPoS – HunPoS (Halacsy et al, 2007) is an open source reimplementation of the statistical part-of-speech tagger Trigrams’n Tags, also called TnT (Brants, 2000) allowing the user to tune the tagger by using different feature settings.
  • Maryam Tavafi POS Tagger – This software includes implementation of a Persian part of speech tagger based on Structured Support Vector Machines.
  • Perstem – Perstem is a Persian (Farsi) stemmer, morphological analyzer, transliterator, and partial part-of-speech tagger. Inflexional morphemes are separated or removed from their stems. Perstem can also tokenize and transliterate between various character set encodings and romanizations.
  • Persianp Toolbox – Multi-purpose persian NLP toolbox.
  • UM-wtlab pos tagger – This software is a C# implementation of the Viberbi and Brill part-of-speech taggers.
  • RDRPOSTagger provides a pre-trained part-of-speech (POS) tagging model for Persian. This POS tagging toolkit is implemented in both Python and Java.
  • jPTDP provides a pre-trained model for joint POS tagging and dependency parsing for Persian.

Language Detection

Tokenization & Segmentation

  • HAZM – Python library for digesting Persian text.
  • polyglot – Natural language pipeline that supports massive multilingual applications (like lokenization (165 languages), language detection (196 languages), named entity recognition (40 languages), part of speech tagging (16 languages), sentiment analysis (136 languages), word embeddings (137 languages), morphological analysis (135 languages), transliteration (69 Languages)).
  • tok-tok – Tok-tok is a fast, simple, multilingual tokenizer(single .pl file).
  • segmental – You can train your model based on plain-text corpus for text segmentation by powerful deep learning platform.
  • Persian Sentence Segmenter and Tokenizer: SeTPer – Regex based sentence segmenter.
  • Farsi-Verb-Tokenizer – Tokenizes Farsi Verbs.

Normalizer And Text Cleaner

  • HAZM – Python library for digesting Persian text.
  • Persian Pre-processor: PrePer – Another signle .pl tools that normals your persian text.
  • virastar – Cleanning up Persian text!.replace double dash to ndash and triple dash to mdash, replace English numbers with their Persian equivalent, correct :;,.?! spacing (one space after and no space before), replace English percent sign to its Persian equivalent and many other normalization. Virastar is written by ruby.
  • Virastyar – A collection of C# libraries for Persian text processing (Spell Checking, Purification, Punctuation Correction, Persian Character Standardization, Pinglish Conversion & …)

Transliterator

  • Perstem – Perstem is a Persian (Farsi) stemmer, morphological analyzer, transliterator, and partial part-of-speech tagger. Inflexional morphemes are separated or removed from their stems. Perstem can also tokenize and transliterate between various character set encodings and romanizations.

Named Entity Recognition

Embeddings

Morphological Analysis

  • polyglot – Natural language pipeline that supports massive multilingual applications (like lokenization (165 languages), language detection (196 languages), named entity recognition (40 languages), part of speech tagging (16 languages), sentiment analysis (136 languages), word embeddings (137 languages), morphological analysis (135 languages), transliteration (69 Languages)).

Stemmer

  • PersianStemmer – (JavaDelphi,C# and Python) – PersianStemmer is a longest-match stemming algorithm that is based on pattern matching. It uses a knowledge base which consist of a collection of rules named “patterns”. Furthermore, the exceptions and problems in the Persian morphology have been studied, and a solution is presented for each of them. So our stemmer evaluated. Its result was much better than the previous stemmers.
  • Perstem – Perstem is a Persian (Farsi) stemmer, morphological analyzer, transliterator, and partial part-of-speech tagger. Inflexional morphemes are separated or removed from their stems. Perstem can also tokenize and transliterate between various character set encodings and romanizations.
  • polyglot – Natural language pipeline that supports massive multilingual applications (like lokenization (165 languages), language detection (196 languages), named entity recognition (40 languages), part of speech tagging (16 languages), sentiment analysis (136 languages), word embeddings (137 languages), morphological analysis (135 languages), transliteration (69 Languages)).

Sentiment Analysis

  • polyglot (polarity) – Natural language pipeline that supports massive multilingual applications (like lokenization (165 languages), language detection (196 languages), named entity recognition (40 languages), part of speech tagging (16 languages), sentiment analysis (136 languages), word embeddings (137 languages), morphological analysis (135 languages), transliteration (69 Languages)).
  • NRC-Persian-Lexicon – NRC Word-Emotion Association Lexicon useful for persian sentiment analysis.

Spell Checking

  • async_faspell -Persian spellchecker. An algorithm that suggests words for misspelled words.

Information Extraction

  • baaz – Open information extraction from Persian web.

Data

Part-of-Speech Tagger

  • Bijankhan Corpus – Bijankhan corpus is a tagged corpus that is suitable for natural language processing research on the Persian (Farsi) language. This collection is gathered form daily news and common texts. In this collection all documents are categorized into different subjects such as political, cultural and so on. Totally, there are 4300 different subjects. The Bijankhan collection contains about 2.6 millions manually tagged words with a tag set that contains 40 Persian POS tags.
  • Mojgan Seraji Corpus – Uppsala Persian Corpus (UPC) is a large, freely available Persian corpus. The corpus is a modified version of the Bijankhan corpus with additional sentence segmentation and consistent tokenization containing 2,704,028 tokens and annotated with 31 part-of-speech tags. The part-of-speech tags are listed with explanations in this table.

Dependency Parsing

  • Persian Syntactic Dependency Treebank – This treebank is supplied for free noncommercial use. For commercial uses feel free to contact us. The number of annotated sentences is 29,982 sentences including samples from almost all verbs of the Persian valency lexicon.
  • Uppsala Persian Dependency Treebank: UPDT – Dependency-based syntactically annotated corpus.
  • Pretrained model
  • Universal Dependencies 1.3 – Multi lingual corpus that holds IOB gold data for dependency parsing
  • HamleDT 3.0 – HArmonized Multi-LanguagE Dependency Treebank is a compilation of existing dependency treebanks (or dependency conversions of other treebanks), transformed so that they all conform to the same annotation style. This version uses Universal Dependencies as the common annotation style.

Text Categorization and Classification

  • Hamshahri – Hamshahri collection is a standard reliable Persian text collection that was used at Cross Language Evaluation Forum (CLEF) during years 2008 and 2009 for evaluation of Persian information retrieval systems.
  • Bijankhan Corpus – Bijankhan corpus is a tagged corpus that is suitable for natural language processing research on the Persian (Farsi) language. This collection is gathered form daily news and common texts. In this collection all documents are categorized into different subjects such as political, cultural and so on. Totally, there are 4300 different subjects. The Bijankhan collection contains about 2.6 millions manually tagged words with a tag set that contains 40 Persian POS tags.

Spell Checking

  • FAspell – FASpell dataset was developed for the evaluation of spell checking algorithms. It contains a set of pairs of misspelled Persian words and their corresponding corrected forms similar to the ASpell dataset used for English.
  • Persian-Spell-checker – We’re collecting persian words’ dictionary (verbs, nouns, and etc.) for Persian spell checker.

Machine Tanslation

Parallel Corpus

  • TEP: Tehran English-Persian Parallel Corpus – First free English-Persian corpus.
  • OPUS: the open parallel corpus – OPUS is a growing collection of translated texts from the web. In the OPUS project we try to convert and align free online data, to add linguistic annotation, and to provide the community with a publicly available parallel corpus. OPUS is based on open source products and the corpus is also delivered as an open content package. We used several tools to compile the current collection. All pre-processing is done automatically. No manual corrections have been carried out.

Monolingual Corpus

  • TMC: Tehran Monolingual Corpus – The Tehran Monolingual Corpus (TMC) is a large-scale Persian monolingual corpus. TMC is suited for Language Modeling and relevant research areas in Natural Language Processing. The corpus is extracted from Hamshahri Corpus and ISNA news agency website. The quality of Hamshahri corpus is improved for language modeling purpose by a series of tokenization and spell-checking steps.
  • VOA Persian Corpus – A medium-sized corpus of 7.9 million words, 2003-2008. The corpus is in the public domain, so no copyright restrictions.

Comparable Corpus

Web Collected

  • W2C – Web to Corpus – Corpora – A set of corpora for 120 languages automatically collected from wikipedia and the web.
  • dotIR Collection – dotIR is a standard Persian test collection that is suitable for evaluation of web information retrieval algorithms in Iranian web.dotIR Contains many Persian web pages including their text, links, metadata, etc that are stored in XML format. It is prepared in such a way to be a good representative of Iranian web.It is A good test bed for evaluation of link based information retrieval algorithms. It includes enough Queries and relevance judgments for a valid evaluation.It is not very large, so that it does not require high processing resources.

IR Ranking Evaluation

  • Hamshahri – Hamshahri collection is a standard reliable Persian text collection that was used at Cross Language Evaluation Forum (CLEF) during years 2008 and 2009 for evaluation of Persian information retrieval systems.

IR Crawling And Linking Evaluation

  • dotIR Collection – dotIR is a standard Persian test collection that is suitable for evaluation of web information retrieval algorithms in Iranian web.dotIR Contains many Persian web pages including their text, links, metadata, etc that are stored in XML format. It is prepared in such a way to be a good representative of Iranian web.It is A good test bed for evaluation of link based information retrieval algorithms. It includes enough Queries and relevance judgments for a valid evaluation.It is not very large, so that it does not require high processing resources.

Stop Word Lists

MISC

  • PersianStemmingDataset – PersianStemmingDataset is consist of two manually stemmed persian corpora and an evalution tools in order to compute stemming evaluatin metrics.
  • PersPred – PersPred, is the first online multilingual syntactic and semantic database of Persian compound verbs (complex predicates), developed by the members of the research unit Mondes iranien et indien (CNRS, Sorbonne Nouvelle, Inalco, EPHE) within the ANR-DFG project PERGRAM (2008-2012) and the LR4.1 work package of the Strand 6 of the Labex Empirical Foundations of Linguistics (EFL).
  • ACL-Wiki Resources for Persian – Another list of resources for Persian computing.

Papers

Contribute

Contributions welcome! Read the contribution guidelines first.

https://github.com/mhbashari/awesome-persian-nlp-ir

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