Open Source Windows Natural Language Processing (NLP) Tools

Natural Language Processing (NLP) Tools for Windows

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Browse free open source Natural Language Processing (NLP) tools and projects for Windows below. Use the toggles on the left to filter open source Natural Language Processing (NLP) tools by OS, license, language, programming language, and project status.

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  • 1
    Virastyar

    Virastyar

    Virastyar is an spell checker for low-resource languages

    Virastyar is a free and open-source (FOSS) spell checker. It stands upon the shoulders of many free/libre/open-source (FLOSS) libraries developed for processing low-resource languages, especially Persian and RTL languages Publications: Kashefi, O., Nasri, M., & Kanani, K. (2010). Towards Automatic Persian Spell Checking. SCICT. Kashefi, O., Sharifi, M., & Minaie, B. (2013). A novel string distance metric for ranking Persian respelling suggestions. Natural Language Engineering, 19(2), 259-284. Rasooli, M. S., Kahefi, O., & Minaei-Bidgoli, B. (2011). Effect of adaptive spell checking in Persian. In NLP-KE Contributors: Omid Kashefi Azadeh Zamanifar Masoumeh Mashaiekhi Meisam Pourafzal Reza Refaei Mohammad Hedayati Kamiar Kanani Mehrdad Senobari Sina Iravanin Mohammad Sadegh Rasooli Mohsen Hoseinalizadeh Mitra Nasri Alireza Dehlaghi Fatemeh Ahmadi Neda PourMorteza
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    Downloads: 706 This Week
    Last Update:
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  • 2
    Stanford CoreNLP

    Stanford CoreNLP

    Stanford CoreNLP, a Java suite of core NLP tools

    CoreNLP is your one stop shop for natural language processing in Java! CoreNLP enables users to derive linguistic annotations for text, including token and sentence boundaries, parts of speech, named entities, numeric and time values, dependency and constituency parses, coreference, sentiment, quote attributions, and relations. CoreNLP currently supports 6 languages, Arabic, Chinese, English, French, German, and Spanish. The centerpiece of CoreNLP is the pipeline. Pipelines take in raw text, run a series of NLP annotators on the text, and produce a final set of annotations. Pipelines produce CoreDocuments, data objects that contain all of the annotation information, accessible with a simple API, and serializable to a Google Protocol Buffer. CoreNLP generates a variety of linguistic annotations, including parts of speech, named entities, dependency parses, and coreference.
    Downloads: 7 This Week
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  • 3
    Ansj Chinese word segmentation

    Ansj Chinese word segmentation

    Ansj word segmentation

    The real java implementation of ict. The word segmentation effect is faster than the open source version of ict. Chinese word segmentation, name recognition, part-of-speech tagging, user-defined dictionary. This is a java implementation of Chinese word segmentation based on n-Gram+CRF+HMM. The word segmentation speed reaches about 2 million words per second (tested under mac air), and the accuracy rate can reach more than 96%. At present, it has realized the functions of Chinese word segmentation, Chinese name recognition, user-defined dictionary, keyword extraction, automatic summarization, and keyword tagging. It can be applied to natural language processing and other aspects, and is suitable for various projects that require high word segmentation effects.
    Downloads: 2 This Week
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  • 4
    compromise

    compromise

    Modest natural-language processing

    Language is complicated and there's a gazillion words. Compromise is a javascript library that interprets and pre-parses text and makes some reasonable decisions so things are way easier. Compromise tries its best to parse text. it is small, quick, and often good-enough. It is not as smart as you'd think. Conjugate and negate verbs in any tense. Play between plural, singular and possessive forms. Interpret plain-text numbers. Handle implicit terms. Use it on the client-side or as an es-module. compromise is 180kb (minified). It's pretty fast. It can run on keypress. It works mainly by conjugating all forms of a basic word list. Decide how words get interpreted or make heavier changes with a compromise-plugin. Parse text without running POS-tagging. Pre-parse any match statements for faster lookups. It is not the most accurate, or clever nlp library, but found its niche as an easy, small library that can run everywhere.
    Downloads: 2 This Week
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  • 5
    TextBlob

    TextBlob

    TextBlob is a Python library for processing textual data

    Simple, Pythonic, text processing, Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more. It provides a simple API for diving into common natural language processing (NLP) tasks such as part-of-speech tagging, noun phrase extraction, sentiment analysis, classification, translation, and more. TextBlob stands on the giant shoulders of NLTK and pattern, and plays nicely with both. Supports word inflection (pluralization and singularization) and lemmatization, as well as spelling correction. Add new models or languages through extensions. Also, it comes with a WordNet integration. If you only intend to use TextBlob’s default models (no model overrides), you can pass the lite argument. This downloads only those corpora needed for basic functionality. TextBlob is also available as a conda package.
    Downloads: 1 This Week
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  • 6
    This project is devoted to the development of natural language processing tools and resources for the Lingala language, which is spoken by tens of millions of people in central Africa.
    Downloads: 1 This Week
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  • 7
    mbFXWords

    mbFXWords

    Analyze text. Diagonal read subject, predicate, obj. Search other pdf.

    Version 1.04. Applies and builds upon Apache OpenNLP. For English, French and German files. JavaFX Application, runs with Oracle Java Runtime Environment version 8 that is including JavaFX. NLP extensions: - Divide sentences in subclauses: segmentation. - Divide plain text: subject, predicate, object. - Count words: stemming. - Search for similar content: pdf's. Gives out subject, predicate and object of sentences of pdf and plain text files. Provides comfortable GUI. Automatic language detection.
    Downloads: 0 This Week
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  • 8
    natural

    natural

    General natural language facilities for node

    "Natural" is a general natural language facility for nodejs. It offers a broad range of functionalities for natural language processing. Tokenizing, stemming, classification, phonetics, tf-idf, WordNet, string similarity, and some inflections are currently supported. It’s still in the early stages, so we’re very interested in bug reports, contributions and the like. Note that many algorithms from Rob Ellis’s node-nltools are being merged into this project and will be maintained from here onward. While most of the algorithms are English-specific, contributors have implemented support for other languages. Russian stemming has been added and Spanish stemming has been added, as well. Stemming and tokenizing in more languages have been added. If you’re just looking to use natural without your own node application, you can install via NPM.
    Downloads: 0 This Week
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