〽️argument mapping platform, a django project

Curated List: Practical Natural Language Processing done in Ruby

Python Keyphrase Extraction module

🥛turkic morphology project

PyNLPl, pronounced as 'pineapple', is a Python library for Natural Language Processing. It contains various modules useful for common, and less common, NLP tasks. PyNLPl can be used for basic tasks such as the extraction of n-grams and frequency lists, and to build simple language model. There are also more complex data types and algorithms. Moreover, there are parsers for file formats common in NLP (e.g. FoLiA/Giza/Moses/ARPA/Timbl/CQL). There are also clients to interface with various NLP specific servers. PyNLPl most notably features a very extensive library for working with FoLiA XML (Format for Linguistic Annotation).

Statistics and accepted paper list of ACL 2020 with arXiv link

BLLIP reranking parser (also known as Charniak-Johnson parser, Charniak parser, Brown reranking parser) See http://pypi.python.org/pypi/bllipparser/ for Python module.

Deep-learning model presented in "DataStories at SemEval-2017 Task 4: Deep LSTM with Attention for Message-level and Topic-based Sentiment Analysis".

Statistical NLG for spoken dialogue systems

Data and software for building the ACL Anthology.

Cantonese Linguistics and NLP in Python

Colibri core is an NLP tool as well as a C++ and Python library for working with basic linguistic constructions such as n-grams and skipgrams (i.e patterns with one or more gaps, either of fixed or dynamic size) in a quick and memory-efficient way. At the core is the tool ``colibri-patternmodeller`` whi ch allows you to build, view, manipulate and query pattern models.

A curated list of NLP resources for Hungarian

FoLiA Linguistic Annotation Tool -- Flat is a web-based linguistic annotation environment based around the FoLiA format (http://proycon.github.io/folia), a rich XML-based format for linguistic annotation. Flat allows users to view annotated FoLiA documents and enrich these documents with new annotations, a wide variety of linguistic annotation types is supported through the FoLiA paradigm.

Abstract Meaning Representation (AMR) tutorial slides

Материалы курса по компьютерной лингвистике Школы Лингвистики НИУ ВШЭ

Curated list of open-access/open-source/off-the-shelf resources and tools developed with a particular focus on German

🙊 WIP software for creating speech recognition models.

Frog is an integration of memory-based natural language processing (NLP) modules developed for Dutch. All NLP modules are based on Timbl, the Tilburg memory-based learning software package.

This repository provides everything to get started with Python for Text Mining / Natural Language Processing (NLP)

Unicode tokeniser. Ucto tokenizes text files: it separates words from punctuation, and splits sentences. It offers several other basic preprocessing steps such as changing case that you can all use to make your text suited for further processing such as indexing, part-of-speech tagging, or machine translation. Ucto comes with tokenisation rules for several languages and can be easily extended to suit other languages. It has been incorporated for tokenizing Dutch text in Frog, our Dutch morpho-syntactic processor. http://ilk.uvt.nl/ucto --

LaMachine - A software distribution of our in-house as well as some 3rd party NLP software - Virtual Machine, Docker, or local compilation/installation script

Python tutorials as Jupyter Notebooks for NLP, ML, AI

FoLiA: Format for Linguistic Annotation - FoLiA is a rich XML-based annotation format for the representation of language resources (including corpora) with linguistic annotations. A wide variety of linguistic annotations are supported, making FoLiA a useful format for NLP tasks and data interchange. Note that the actual Python library for processing FoLiA is implemented as part of PyNLPl, this contains higher-level tools that use the library as well as the full documentation, validation schemas, and set definitions

Sentiment analysis of tweets in Russian using Convolutional Neural Networks (CNN) with Word2Vec embeddings.

Google News and Leo Tolstoy: Visualizing Word2Vec Word Embeddings using t-SNE.

Yet Another (natural language) Parser