Modern XMPP, with a JSON API

The Classical Language Toolkit

💥 Use the latest Stanza (StanfordNLP) research models directly in spaCy

CUI-based Tree Visualizer for Universal Dependencies and Immediate Catena Analysis

Free hands-on course with the implementation (in Python) and description of several Natural Language Processing (NLP) algorithms and techniques, on several modern platforms and libraries.

Pipeline component for spaCy (and other spaCy-wrapped parsers such as spacy-stanza and spacy-udpipe) that adds CoNLL-U properties to a Doc and its sentences and tokens. Can also be used as a command-line tool.

Model training tutorials for the Stanza Python NLP Library

Novoic's linguistic feature extraction library

More machine friendly storage of OCLC's EZProxy Database Stanzas

A Summer project that converts text to Indian Sign language through animation

An easy-to-use library to linguistically compare one sentence and its words to another, in the same language or a different one. For instance useful for comparing a translation with the original text, to find differences and similarities between two different translations, or to see how a machine translation differs from a reference translation.

Rust-based Natural Language Toolkit using Python Bindings

ThamizhiMorph: A Tamil Morphological Analyser and Generator

NLP Preprocessing Pipeline Wrappers

PipelineIE is a project that contains a pipeline for information extraction (currently triple) from free text and domain specific text (eg. biomedical domain) and also supports custom models making it flexible to support other domains. It takes care of coreference resolution and entity resolution by also allowing to test with different tools.

Prototype changelog stanza for @Homebrew Casks and formulae.

ThamizhiPOSt - A neural based POS tagger for Tamil

unsupervised process of identifying topics in a set of persian songs by LDA method of topic modelling

NLP basic and advance text preprocessing concepts and techniques

A library for introducing different metrics for measuring linguistic complexity.