Open Source Natural Language Processing (NLP) Tools - Page 4

Natural Language Processing (NLP) Tools

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  • 1
    AllenNLP

    AllenNLP

    An open-source NLP research library, built on PyTorch

    AllenNLP makes it easy to design and evaluate new deep learning models for nearly any NLP problem, along with the infrastructure to easily run them in the cloud or on your laptop. AllenNLP includes reference implementations of high quality models for both core NLP problems (e.g. semantic role labeling) and NLP applications (e.g. textual entailment). AllenNLP supports loading "plugins" dynamically. A plugin is just a Python package that provides custom registered classes or additional allennlp subcommands. There is ecosystem of open source plugins, some of which are maintained by the AllenNLP team here at AI2, and some of which are maintained by the broader community. AllenNLP will automatically find any official AI2-maintained plugins that you have installed, but for AllenNLP to find personal or third-party plugins you've installed, you also have to create either a local plugins file named .allennlp_plugins in the directory where you run the allennlp command.
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  • 2
    AminePlatform

    AminePlatform

    Amine is a Multi-Layer Platform for the dev. of Intelligent Systems

    Amine is an Artificial Intelligence Multi-Layer Java Open Source Platform dedicated to the development of various kinds of Intelligent Systems and Agents (Knowledge-Based, Ontology-Based, Conceptual Graph -CG- Based, NLP, Reasoning and Learning, Natural Language Processing, etc.). Ontology, KB can be created and manipulated with various processes. CG theory is used as the main knowledge representation language. Amine provides two languages: PROLOG+CG which extends PROLOG with CG and Amine modules, and SYNERGY which is a visual activation/propagation based language. CGs are considered by SYNERGY as activable/executable graphs. See for more detail: //amine-platform.sourceforge.net/
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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.
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  • 4
    Apache OpenNLP

    Apache OpenNLP

    Apache OpenNLP

    Apache OpenNLP is a machine learning-based NLP library that provides tools for text-processing tasks such as tokenization, sentence segmentation, and named entity recognition.
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  • 5

    Aseryla2

    Aseryla2 code repositories

    This project describes a model of how the semantic human memory represents the information relevant to the objects of the world in text format. It provides a system and a GUI application capable of extracting and managing concepts and relations from English texts. https://aseryla2.sourceforge.io/
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  • 6
    AutoGPTQ

    AutoGPTQ

    An easy-to-use LLMs quantization package with user-friendly apis

    AutoGPTQ is an implementation of GPTQ (Quantized GPT) that optimizes large language models (LLMs) for faster inference by reducing their computational footprint while maintaining accuracy.
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  • 7
    AutoSummary uses Natural Language Processing to generate a contextually-relevant synopsis of plain text. It uses statistical and rule-based methods for part-of-speech tagging, word sense disambiguation, sentence deconstruction and semantic analysis.
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  • 8
    Automatic text summarizer

    Automatic text summarizer

    Module for automatic summarization of text documents and HTML pages

    Sumy is an automatic text summarization library that provides multiple algorithms for extracting key content from documents and articles. Simple library and command line utility for extracting summary from HTML pages or plain texts. The package also contains a simple evaluation framework for text summaries. Implemented summarization methods are described in the documentation. I also maintain a list of alternative implementations of the summarizers in various programming languages.
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  • 9
    Awesome Fraud Detection Research Papers

    Awesome Fraud Detection Research Papers

    A curated list of data mining papers about fraud detection

    A curated list of data mining papers about fraud detection from several conferences.
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  • 10
    Awesome Recurrent Neural Networks

    Awesome Recurrent Neural Networks

    A curated list of resources dedicated to RNN

    A curated list of resources dedicated to recurrent neural networks (closely related to deep learning). Provides a wide range of works and resources such as a Recurrent Neural Network Tutorial, a Sequence-to-Sequence Model Tutorial, Tutorials by nlintz, Notebook examples by aymericdamien, Scikit Flow (skflow) - Simplified Scikit-learn like Interface for TensorFlow, Keras (Tensorflow / Theano)-based modular deep learning library similar to Torch, char-rnn-tensorflow by sherjilozair, char-rnn in tensorflow, and much more. Codes, theory, applications, and datasets about natural language processing, robotics, computer vision, and much more.
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  • 11
    BEIR

    BEIR

    A Heterogeneous Benchmark for Information Retrieval

    BEIR is a benchmark framework for evaluating information retrieval models across various datasets and tasks, including document ranking and question answering.
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  • 12

    Be-project

    Named Entity Identifier.

    An NLP based domain specific Named Entity Identifier that uses supervised and semi-supervised learning techniques to make context based identification.
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  • 13

    Bermuda Text-to-Speech

    This project includes basic NLP and DSP techniques for Text-to-Speech

    See TTS demo at: http://rslp.racai.ro/index.php?page=tts This is an entirely written in JAVA project which includes a set of tools and methods designed to enable Multilingual Text-to-Speech (TTS) synthesis. We currently support English and Romanian but we will soon train more models and make them available for download. If you want to read more about our other NLP and TTS tools check out http://nlptools.racai.ro.
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  • 14
    BettaFish

    BettaFish

    Public opinion analysis system

    BettaFish is an open-source, multi-agent public opinion analysis system built to automate the collection, deep analysis, and reporting of social media data at scale through conversational queries. It uses a modular architecture of specialized agents that collaborate to crawl mainstream platforms, extract multimodal content like text and short video, and synthesize insights through both statistical and large language model techniques. With a design that lets users pose questions in natural language and receive structured reports, charts, and visualizations, the system aims to break information cocoons and provide comprehensive views of trends and public sentiment. Unlike simpler analytics tools, BettaFish employs agent collaboration and a “forum” style internal mechanism to combine diverse model outputs, making the analysis richer and more robust. It also integrates multimodal processing, enabling it to parse images and video alongside text.
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  • 15

    BibleNLP

    Natural Language Processing using The Holy Bible

    This project attempts to develop natural language processing routines as applied to a Bible text domain. Many common technologies (e.g., tokenization, Brill POS tagger) are used in conjunction with theoretical paradigms (e.g., hierarchical word definition trees, phrasal concordance).
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  • 16
    This is a Java-based project for complex event extraction from text and co-reference resolution. Currently the code can read BioNLP shared task format (http://2011.bionlp-st.org/) and i2b2 Natural Language Processing for Clinical Data shared task format (https://www.i2b2.org/NLP/DataSets/Main.php). Event extraction includes finding events and the parameters for an event in a text. The method is based on SVM but other ML algorithms can be adopted. The method details are explained in the following paper: Ehsan Emadzadeh, Azadeh Nikfarjam, and Graciela Gonzalez. 2011. Double Layered Learning for Biological Event Extraction from Text. In Proceedings of the BioNLP 2011 Workshop Companion Volume for Shared Task, Portland, Oregon, June. Association for Computational Linguistic
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  • 17
    BioNLP is an initiative by the University of Colorado Denver Health Sciences Center to create and distribute code, software, and data for applying natural language processing techniques to biomedical texts
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  • 18
    The BioNLP UIMA Component Repository provides UIMA wrappers for novel and well-known 3rd-party NLP tools used in biomedical text prosessing, such as tokenizers, parsers, named entity taggers, and tools for evaluation.
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  • 19
    Birbal is an AI project for giving answers to common question.It uses natural language processing for accepting queries in any form.it searches for most appropriate answers in database.Project comprises user guided learning process.
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  • 20
    Bolt NLP

    Bolt NLP

    Bolt is a deep learning library with high performance

    Bolt is a high-performance deep learning inference framework developed by Huawei Noah's Ark Lab. It is designed to optimize and accelerate the deployment of deep learning models across various hardware platforms. Bolt is a light-weight library for deep learning. Bolt, as a universal deployment tool for all kinds of neural networks, aims to automate the deployment pipeline and achieve extreme acceleration. Bolt has been widely deployed and used in many departments of HUAWEI company, such as 2012 Laboratory, CBG and HUAWEI Product Lines. If you have questions or suggestions, you can submit issue.
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  • 21
    BotSharp

    BotSharp

    AI Multi-Agent Framework in .NET

    Conversation as a platform (CaaP) is the future, so it's perfect that we're already offering the whole toolkits to our .NET developers using the BotSharp AI BOT Platform Builder to build a CaaP. It opens up as much learning power as possible for your own robots and precisely control every step of the AI processing pipeline. BotSharp is an open source machine learning framework for AI Bot platform builder. This project involves natural language understanding, computer vision and audio processing technologies, and aims to promote the development and application of intelligent robot assistants in information systems. Out-of-the-box machine learning algorithms allow ordinary programmers to develop artificial intelligence applications faster and easier. It's written in C# running on .Net Core that is full cross-platform framework. C# is a enterprise-grade programming language which is widely used to code business logic in information management-related system.
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  • 22
    Botkit

    Botkit

    Tool for building chat bots, apps and custom integrations

    An open source developer tool for building chat bots, apps and custom integrations for major messaging platforms. Part of the Microsoft Bot Framework. We love bots, and want to make them easy and fun to build! Include Botkit into your Node application and boot up a controller that will define your bot's behaviors. In this case, we're setting up a bot to use with the Bot Framework Emulator. Tell the bot to listen for users saying "hello," and use `bot.reply` to send an immediate response. Start a conversation, then queue up multiple messages to send, including a prompt sent using `convo.ask()` which allows your bot to capture user input and use it. Botkit is just one part of a bigger set of developer tools and SDKs that encompass the Microsoft Bot Framework. The Bot Framework SDK provides the base upon which Botkit is built. It is available in multiple programming languages!
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  • 23
    The Bracket Based Arabic Annotation (B2A2) scheme provides users with the ability to manually tag Arabic text with Part-of-Speech (POS) markers. B2A2 introduces a new approach that enables tagging Arabic text using morphology aware tag markers. Different types of tag markers can be incorporated e.g. grammatical, functional, semantic, linguistic markers.Tag-sets can be configured (modified/extended) by accessing the related table in the supporting database, The user can upload text files where sentences are normalized and inserted into the supporting database. Multiple narratives can be listed in the text file, where narratives are separated using a # symbol. The text upload process entitles the initial (POS) tagging of uploaded text using Stanford (POS) tagger. The user can later modify and extend the initial tagging. The resultant annotations are stored in the supporting database. These results can be exported to excel or text files for further processing.
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  • 24
    CC-Net

    CC-Net

    Tools to download and cleanup Common Crawl data

    cc_net provides tools to download, segment, clean, and filter Common Crawl to build large-scale text corpora, including monolingual datasets and the multilingual CC-100 collection introduced in the associated paper. It includes pipelines to fetch snapshots, extract text, de-duplicate, identify language, and apply quality filtering based on heuristics and language models. The outputs are intended for pretraining language models and for creating standardized corpora that can be reproduced or updated with new crawls. The repository documents practical concerns like HTTP failures, snapshot differences, and stats JSONs, reflecting community use across many languages. While powerful, the repo has been archived and is read-only, so users should expect to run it as-is or fork for maintenance. Even in archived state, issues and releases pages remain useful references for implementation details and dataset lineage.
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  • 25
    CCASH
    CCASH (Cost-Conscious Annotation Supervised by Humans) is a web application framework designed to facilitate the development and application of cost-efficient annotation methods. It is currently being developed by the NLP group at BYU.
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