franc - Natural language detection

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Detect the language of text.† - Based on the UDHR, the most translated document in the world.

natural-language language-detection nlp natural language detection detect

pynlpl - PyNLPl, pronounced as 'pineapple', is a Python library for Natural Language Processing

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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 Annotatation). The library is a divided into several packages and modules. It works on Python 2.7, as well as Python 3.

nlp computational-linguistics linguistics library folia machine-learning language-modelling search-algorithms evaluation-metrics text-processing nlp-library natural-language-processing

spark-nlp - Natural Language Understanding Library for Apache Spark.

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John Snow Labs Spark-NLP is a natural language processing library built on top of Apache Spark ML. It provides simple, performant & accurate NLP annotations for machine learning pipelines, that scale easily in a distributed environment. This library has been uploaded to the spark-packages repository https://spark-packages.org/package/JohnSnowLabs/spark-nlp .

nlp nlu natural-language-processing natural-language-understanding spark spark-ml pyspark machine-learning named-entity-recognition sentiment-analysis lemmatizer spell-checker tokenizer entity-extraction stemmer part-of-speech-tagger annotation-framework

nlp-architect - NLP Architect by Intel AI Lab: Python library for exploring the state-of-the-art deep learning topologies and techniques for natural language processing and natural language understanding

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NLP Architect is an open-source Python library for exploring state-of-the-art deep learning topologies and techniques for natural language processing and natural language understanding. It is intended to be a platform for future research and collaboration. Framework documentation on NLP models, algorithms, and modules, and instructions on how to contribute can be found at our main documentation site.

deeplearning nlp nlu tensorflow dynet keras

NTextCat

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NTextCat is text classification utility. Primary target is language identification. So it helps you to recognize (identify) the language of text (or binary) snippet. Pure .net application (C#).

categorization classification identification language language-processing natural-language nlp

nlp-with-ruby - Practical Natural Language Processing done in Ruby.

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This curated list comprises awesome resources, libraries, information sources about computational processing of texts in human languages with the Ruby programming language. That field is often referred to as NLP, Computational Linguistics, HLT (Human Language Technology) and can be brought in conjunction with Artificial Intelligence, Machine Learning, Information Retrieval, Text Mining, Knowledge Extraction and other related disciplines. This list comes from our day to day work on Language Models and NLP Tools. Read why this list is awesome. Our FAQ describes the important decisions and useful answers you may be interested in.

machine-learning natural-language-processing nlp sentiment-analysis pos-tag awesome awesome-list list computational-linguistics rubynlp rubyml

nlp_tasks - Natural Language Processing Tasks and References

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I've been working on several natural language processing tasks for a long time. One day, I felt like drawing a map of the NLP field where I earn a living. I'm sure I'm not the only person who wants to see at a glance which tasks are in NLP. Reviewed and updated by YJ Choe on Oct. 18, 2017.

language natural-language-processing nlp

spaCy - 💫 Industrial-strength Natural Language Processing (NLP) with Python and Cython

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spaCy is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products. spaCy comes with pre-trained statistical models and word vectors, and currently supports tokenization for 20+ languages. It features the fastest syntactic parser in the world, convolutional neural network models for tagging, parsing and named entity recognition and easy deep learning integration. It's commercial open-source software, released under the MIT license. 💫 Version 2.0 out now! Check out the new features here.

natural-language-processing data-science big-data machine-learning cython nlp artificial-intelligence ai spacy nlp-library neural-network neural-networks deep-learning

TextCat - Perl Program helps to identify natural language

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TextCat written in Perl helps to identify 69 natural langauge.

language-identification language-detection text-catagorization

awesome-nlp - :book: A curated list of resources dedicated to Natural Language Processing (NLP)

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Please read the contribution guidelines before contributing. Please feel free to create pull requests.

natural-language-processing deep-learning machine-learning language awesome awesome-list nlp text-mining

PyTorch-NLP - Supporting Rapid Prototyping with a Toolkit (incl. Datasets and Neural Network Layers)

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PyTorch-NLP, or torchnlp for short, is a library of neural network layers, text processing modules and datasets designed to accelerate Natural Language Processing (NLP) research. Join our community, add datasets and neural network layers! Chat with us on Gitter and join the Google Group, we're eager to collaborate with you.

pytorch nlp natural-language-processing pytorch-nlp torchnlp data-loader embeddings word-vectors deep-learning dataset metrics neural-network sru machine-learning

nlpnet - A neural network architecture for NLP tasks, inspired in the SENNA system

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Gitter is chat room for developers. nlpnet is a Python library for Natural Language Processing tasks based on neural networks. Currently, it performs part-of-speech tagging, semantic role labeling and dependency parsing. Most of the architecture is language independent, but some functions were specially tailored for working with Portuguese. This system was inspired by SENNA.

nlp natural-language-processing neural-network pos-tagging semantic-role-labeling parsing

UIMA - Unstructured information management architecture

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UIMA analyzes large volumes of unstructured information in order to discover knowledge that is relevant to an end user. It is a framework with different set of components. The components include Language Identification, Language specific segmentation, Sentence boundary detection, Entity detection (person/place names) etc. The framework manages these components and the data flows between them.

document-pipeline connector content-connector text-extraction document-processing unstructured

decaNLP - The Natural Language Decathlon: A Multitask Challenge for NLP

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The Natural Language Decathlon is a multitask challenge that spans ten tasks: question answering (SQuAD), machine translation (IWSLT), summarization (CNN/DM), natural language inference (MNLI), sentiment analysis (SST), semantic role labeling(QA‑SRL), zero-shot relation extraction (QA‑ZRE), goal-oriented dialogue (WOZ, semantic parsing (WikiSQL), and commonsense reasoning (MWSC). Each task is cast as question answering, which makes it possible to use our new Multitask Question Answering Network (MQAN). This model jointly learns all tasks in decaNLP without any task-specific modules or parameters in the multitask setting. For a more thorough introduction to decaNLP and the tasks, see the main website, our blog post, or the paper. While the research direction associated with this repository focused on multitask learning, the framework itself is designed in a way that should make single-task training, transfer learning, and zero-shot evaluation simple. Similarly, the paper focused on multitask learning as a form of question answering, but this framework can be easily adapted for different approached to single-task or multitask learning.

deep-learning natural-language-processing multitask-learning

ruby-nlp - A collection of links to Ruby Natural Language Processing (NLP) libraries, tools and software

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A collection of Natural Language Processing (NLP) Ruby libraries, tools and software. Suggestions and contributions are welcome. Client libraries to various 3rd party NLP API services.

gt-nlp-class - Course materials for Georgia Tech CS 4650 and 7650, "Natural Language"

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This course gives an overview of modern data-driven techniques for natural language processing. The course moves from shallow bag-of-words models to richer structural representations of how words interact to create meaning. At each level, we will discuss the salient linguistic phemonena and most successful computational models. Along the way we will cover machine learning techniques which are especially relevant to natural language processing. Readings will be drawn mainly from my notes. Additional readings may be assigned from published papers, blogposts, and tutorials.

TextBlob - Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more

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TextBlob is a Python (2 and 3) library for processing textual data. 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.

nlp nltk pattern python-3 python-2 natural-language-processing

jchardet - Charset detection algorithm in Java

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jchardet is a java port of the source from mozilla's automatic charset detection algorithm.

language-identification language-detection text-catagorization internation alization

gensim - Topic Modelling for Humans

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Gensim is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. Target audience is the natural language processing (NLP) and information retrieval (IR) community. If this feature list left you scratching your head, you can first read more about the Vector Space Model and unsupervised document analysis on Wikipedia.

gensim topic-modeling information-retrieval machine-learning natural-language-processing nlp data-science data-mining word2vec word-embeddings text-summarization neural-network document-similarity word-similarity fasttext

sling - SLING - A natural language frame semantics parser

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SLING is a parser for annotating text with frame semantic annotations. It is trained on an annotated corpus using Tensorflow and Dragnn.The parser is a general transition-based frame semantic parser using bi-directional LSTMs for input encoding and a Transition Based Recurrent Unit (TBRU) for output decoding. It is a jointly trained model using only the text tokens as input and the transition system has been designed to output frame graphs directly without any intervening symbolic representation.

natural-language-understanding natural-language-processing neural-network machine-learning jit-compiler frame-semantic-parsing nlp