Open Source Linux Natural Language Processing (NLP) Tools - Page 7
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Natural Language Processing (NLP) Tools for Linux
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Loan management software that makes it easy.Bryt Software is ideal for lending professionals who are looking for a feature rich loan management system that is intuitive and easy to use. We are 100% cloud-based, software as a service. We believe in providing our customers with fair and honest pricing. Our monthly fees are based on your number of users and we have a minimal implementation charge.
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JWNL is a Java API for accessing the WordNet relational dictionary. WordNet is widely used for developing NLP applications, and a Java API such as JWNL will allow developers to more easily use Java for building NLP applications.
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JWebPro: A Java tool that can interact with Google search and then process the returned Web documents in a couple of ways. The outputs can serve as inputs for NLP, IR, infor extraction, Web mining, online social network extraction/analysis applications.
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Kener
Kener is a Modern Self hosted Status Page, batteries included
Kener: Open-source Node.js status page tool, designed to make service monitoring and incident handling a breeze. It offers a sleek and user-friendly interface that simplifies tracking service outages and improves how we communicate during incidents. And the best part? Kener integrates seamlessly with GitHub, making incident management a team effort—making it easier for us to track and fix issues together in a collaborative and friendly environment. -
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KoGPT
KakaoBrain KoGPT (Korean Generative Pre-trained Transformer)
KoGPT is a Korean language model based on OpenAI’s GPT architecture, designed for various natural language processing (NLP) tasks such as text generation, summarization, and dialogue systems. -
SoftCo: Enterprise Invoice and P2P Automation SoftwareSoftCo Accounts Payable Automation processes all PO and non-PO supplier invoices electronically from capture and matching through to invoice approval and query management. SoftCoAP delivers unparalleled touchless automation by embedding AI across matching, coding, routing, and exception handling to minimize the number of supplier invoices requiring manual intervention. The result is 89% processing savings, supported by a context-aware AI Assistant that helps users understand exceptions, answer questions, and take the right action faster.
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KoNLPy
Python package for Korean natural language processing
KoNLPy is a natural language processing (NLP) library for the Korean language, offering tokenization, morphological analysis, and named entity recognition. -
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A language modeling tool kit written in Java for natural language processing applications. It can handle character-by-character modeling of unknown words, language model combination, comparison, and evaluation, as well as a number of smoothing techniques
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LightAutoML
Fast and customizable framework for automatic ML model creation
LightAutoML is an automated machine learning (AutoML) framework optimized for efficient model training and hyperparameter tuning, focusing on both tabular and text data. -
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Lingua-Go
The most accurate natural language detection library for Go
Lingua-Go is a Golang implementation of the Lingua language detection library, providing efficient and accurate language identification for Go-based applications. Its task is simple: It tells you which language some text is written in. This is very useful as a preprocessing step for linguistic data in natural language processing applications such as text classification and spell checking. Other use cases, for instance, might include routing e-mails to the right geographically located customer service department, based on the e-mails' languages. Language detection is often done as part of large machine-learning frameworks or natural language processing applications. In cases where you don't need the full-fledged functionality of those systems or don't want to learn the ropes of those, a small flexible library comes in handy. -
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Lingua-Py
The most accurate natural language detection library for Python
Its task is simple: It tells you which language some text is written in. This is very useful as a preprocessing step for linguistic data in natural language processing applications such as text classification and spell checking. Other use cases, for instance, might include routing e-mails to the right geographically located customer service department, based on the e-mails' languages. Language detection is often done as part of large machine learning frameworks or natural language processing applications. In cases where you don't need the full-fledged functionality of those systems or don't want to learn the ropes of those, a small flexible library comes in handy. -
Turn traffic into pipeline and prospects into customersDocket is an AI-powered sales enablement platform designed to unify go-to-market (GTM) data through its proprietary Sales Knowledge Lake™ and activate it with intelligent AI agents. The platform helps marketing teams increase pipeline generation by 15% by engaging website visitors in human-like conversations and qualifying leads. For sales teams, Docket improves seller efficiency by 33% by providing instant product knowledge, retrieving collateral, and creating personalized documents. Built for GTM teams, Docket integrates with over 100 tools across the revenue tech stack and offers enterprise-grade security with SOC 2 Type II, GDPR, and ISO 27001 compliance. Customers report improved win rates, shorter sales cycles, and dramatically reduced response times. Docket’s scalable, accurate, and fast AI agents deliver reliable answers with confidence scores, empowering teams to close deals faster.
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Lingua-RS
The most accurate natural language detection library for Rust
Lingua-RS is a language detection library implemented in Rust, designed to accurately identify the language of given text samples. It tells you which language some text is written in. This is very useful as a preprocessing step for linguistic data in natural language processing applications such as text classification and spell checking. Other use cases, for instance, might include routing e-mails to the right geographically located customer service department, based on the e-mails' languages. -
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The Lingual Quanta is an organization created by software engineers that are interested in Natural Language Processing technologies focused in libraries useful for projects such as grammar checkers, text markups etc.
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LoonyBin is a workflow management system specifically geared toward the needs of computational research. It is currently used in Natural Language Processing and statistical machine translation. More at http://www.cs.cmu.edu/~jhclark/loonybin/.
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This is a toolkit for medical natural language processing (NLP). The core engine is general enough to be used in a variety of text processing domains, though the toolkit includes specific support for medical reports and patient de-identification.
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MITRE Annotation Toolkit
A toolkit for managing and manipulating text annotations
The MITRE Annotation Toolkit (MAT) is a suite of tools which can be used for automated and human tagging of annotations. Annotation is a process, used mostly by researchers in natural language processing, of enhancing documents with information about the various phrase types the documents contain. MAT supports both UI interaction and command-line interaction, and provides various levels of control over the overall annotation process. It can be customized for specific tasks (e.g., named entity identification, de-identification of medical records). The goal of MAT is not to help you configure your training engine (in the default case, the Carafe CRF system) to achieve the best possible performance on your data. MAT is for "everything else": all the tools you end up wishing you had. -
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The MOJO NLP platform is a set of tools designed to tackle Natural Language Processing challenges. This project includes MojoMapper, an automated medical concept identification system and MojoSpell, a spell checker to handle medical language.
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MTBook
Machine Translation: Foundations and Models
This is a tutorial, the purpose is to introduce the basic knowledge and modeling methods of machine translation systematically, and on this basis, discuss some cutting-edge technologies of machine translation (formerly known as "Machine Translation: Statistical Modeling and Deep Learning") method"). Its content is compiled into a book, which can be used for the study of senior undergraduates and graduate students in computer and artificial intelligence related majors, and can also be used as reference material for researchers related to natural language processing, especially machine translation. This book is written in tex, and all source codes are open. This book is divided into four parts, each of which consists of several chapters. The order of the chapters refers to the time context of the development of machine translation technology, while taking into account the internal logic of the machine translation knowledge system. -
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MadeNLP
Multi-agent Development Environment for Natural Language Processing
Multi-agent Development Environment for Natural Language Processing Java Based System Development framework -
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Medical Treebank
Community-based linguistic annotation work on clinical documents.
This project hosts linguistic annotations and guidelines for clinical text. We plan to include several types of annotation (Token, POS and Parse) in WordFreak format on clinical notes originally from the i2b2/VA NLP challenges. The guidelines are copyrighted, but free for the community to use. Annotation in WordFreak format contains only linguistic labels and character offsets, and can be distributed independently from the note text. Instruction is provided on setting up WordFreak for aligning/visualizing the annotations with the source text, which should be obtained through the official i2b2 data host https://www.i2b2.org/NLP/DataSets/Main.php. -
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Metafrastes is a natural language processing system that can take an input query from the user and translate that internally in order to communicate with a knowledge base in the form of an ontology.
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Milvus Bootcamp
Dealing with all unstructured data, such as reverse image search
Milvus Bootcamp is a collection of tutorials, examples, and best practices for using Milvus, an open-source vector database designed for AI-powered similarity search and retrieval applications. -
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MindNLP
Easy-to-use and high-performance NLP and LLM framework
MindNLP is a natural language processing library built on the MindSpore framework, providing tools and models for various NLP tasks. -
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MARF is a general cross-platform framework with a collection of algorithms for audio (voice, speech, and sound) and natural language text analysis and recognition along with sample applications (identification, NLP, etc.) of its use, implemented in Java.
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This project aims to build a suite of Natural Language Processing tools. Modules will include corpus indexing and access tools, a part-of-speech tagger, tokenisers, text classification software, etc.
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MutationFinder is a biomedical natural language processing (NLP) system for extracting mentions of point mutations from free text. MutationFinder achieves high performance (99% precision, 81% recall on blind test data) as an information extraction system
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NLG-Eval
Evaluation code for various unsupervised automated metrics
NLG-Eval is a toolkit for evaluating the quality of natural language generation (NLG) outputs using multiple automated metrics such as BLEU, METEOR, and ROUGE.
