👍🏻 表库
==========

语言库
------

Node.js 和 Javascript
~~~~~~~~~~~~~~~~~~~~~

   Node.js NLP 的库

-  `Twitter-text <https://github.com/twitter/twitter-text>`__ - Twitter
   的文本处理库的 JavaScript 实现
-  `Knwl.js <https://github.com/benhmoore/Knwl.js>`__ - JS
   中的自然语言处理器
-  `Retext <https://github.com/retextjs/retext>`__ -
   用于分析和操纵自然语言的可扩展系统
-  `NLP Compromise <https://github.com/spencermountain/compromise>`__ -
   浏览器中的自然语言处理
-  `Natural <https://github.com/NaturalNode/natural>`__ -
   节点的一般自然语言设施
-  `Poplar <https://github.com/synyi/poplar>`__ -
   用于自然语言处理（NLP）的基于 Web 的注释工具

Python
~~~~~~

   Python NLP 库

-  `TextBlob <http://textblob.readthedocs.org/>`__ - Providing a
   consistent API for diving into common natural language processing
   (NLP) tasks. Stands on the giant shoulders of `Natural Language
   Toolkit (NLTK) <https://www.nltk.org/>`__ and
   `Pattern <https://github.com/clips/pattern>`__, and plays nicely with
   both :+1:
-  `spaCy <https://github.com/explosion/spaCy>`__ - Industrial strength
   NLP with Python and Cython :+1:

   -  `textacy <https://github.com/chartbeat-labs/textacy>`__ - Higher
      level NLP built on spaCy

-  `gensim <https://radimrehurek.com/gensim/index.html>`__ - Python
   library to conduct unsupervised semantic modelling from plain text
   :+1:
-  `scattertext <https://github.com/JasonKessler/scattertext>`__ -
   Python library to produce d3 visualizations of how language differs
   between corpora
-  `AllenNLP <https://github.com/allenai/allennlp>`__ - An NLP research
   library, built on PyTorch, for developing state-of-the-art deep
   learning models on a wide variety of linguistic tasks.
-  `PyTorch-NLP <https://github.com/PetrochukM/PyTorch-NLP>`__ - NLP
   research toolkit designed to support rapid prototyping with better
   data loaders, word vector loaders, neural network layer
   representations, common NLP metrics such as BLEU
-  `Rosetta <https://github.com/columbia-applied-data-science/rosetta>`__
   - Text processing tools and wrappers (e.g. Vowpal Wabbit)
-  `PyNLPl <https://github.com/proycon/pynlpl>`__ - Python Natural
   Language Processing Library. General purpose NLP library for Python.
   Also contains some specific modules for parsing common NLP formats,
   most notably for `FoLiA <https://proycon.github.io/folia/>`__, but
   also ARPA language models, Moses phrasetables, GIZA++ alignments.
-  `jPTDP <https://github.com/datquocnguyen/jPTDP>`__ - A toolkit for
   joint part-of-speech (POS) tagging and dependency parsing. jPTDP
   provides pre-trained models for 40+ languages.
-  `BigARTM <https://github.com/bigartm/bigartm>`__ - a fast library for
   topic modelling
-  `Snips NLU <https://github.com/snipsco/snips-nlu>`__ - A production
   ready library for intent parsing
-  `Chazutsu <https://github.com/chakki-works/chazutsu>`__ - A library
   for downloading&parsing standard NLP research datasets
-  `Word Forms <https://github.com/gutfeeling/word_forms>`__ - Word
   forms can accurately generate all possible forms of an English word
-  `Multilingual Latent Dirichlet Allocation
   (LDA) <https://github.com/ArtificiAI/Multilingual-Latent-Dirichlet-Allocation-LDA>`__
   - A multilingual and extensible document clustering pipeline
-  `NLP Architect <https://github.com/NervanaSystems/nlp-architect>`__ -
   A library for exploring the state-of-the-art deep learning topologies
   and techniques for NLP and NLU
-  `Flair <https://github.com/zalandoresearch/flair>`__ - A very simple
   framework for state-of-the-art multilingual NLP built on PyTorch.
   Includes BERT, ELMo and Flair embeddings.
-  `Kashgari <https://github.com/BrikerMan/Kashgari>`__ - Simple,
   Keras-powered multilingual NLP framework, allows you to build your
   models in 5 minutes for named entity recognition (NER),
   part-of-speech tagging (PoS) and text classification tasks. Includes
   BERT and word2vec embedding.

C++
~~~

   C++ 库

-  `MIT Information Extraction
   Toolkit <https://github.com/mit-nlp/MITIE>`__ - C, C++, and Python
   tools for named entity recognition and relation extraction
-  `CRF++ <https://taku910.github.io/crfpp/>`__ - Open source
   implementation of Conditional Random Fields (CRFs) for
   segmenting/labeling sequential data & other Natural Language
   Processing tasks.
-  `CRFsuite <http://www.chokkan.org/software/crfsuite/>`__ - CRFsuite
   is an implementation of Conditional Random Fields (CRFs) for labeling
   sequential data.
-  `BLLIP Parser <https://github.com/BLLIP/bllip-parser>`__ - BLLIP
   Natural Language Parser (also known as the Charniak-Johnson parser)
-  `colibri-core <https://github.com/proycon/colibri-core>`__ - C++
   library, command line tools, and Python binding for extracting and
   working with basic linguistic constructions such as n-grams and
   skipgrams in a quick and memory-efficient way.
-  `ucto <https://github.com/LanguageMachines/ucto>`__ - Unicode-aware
   regular-expression based tokenizer for various languages. Tool and
   C++ library. Supports FoLiA format.
-  `libfolia <https://github.com/LanguageMachines/libfolia>`__ - C++
   library for the `FoLiA format <https://proycon.github.io/folia/>`__
-  `frog <https://github.com/LanguageMachines/frog>`__ - Memory-based
   NLP suite developed for Dutch: PoS tagger, lemmatiser, dependency
   parser, NER, shallow parser, morphological analyzer.
-  `MeTA <https://github.com/meta-toolkit/meta>`__ - `MeTA : ModErn Text
   Analysis <https://meta-toolkit.org/>`__ is a C++ Data Sciences
   Toolkit that facilitates mining big text data.
-  `Mecab (Japanese) <https://taku910.github.io/mecab/>`__
-  `Moses <http://statmt.org/moses/>`__
-  `StarSpace <https://github.com/facebookresearch/StarSpace>`__ - a
   library from Facebook for creating embeddings of word-level,
   paragraph-level, document-level and for text classification

Java
~~~~

   Java NLP 库

-  `Stanford NLP <https://nlp.stanford.edu/software/index.shtml>`__
-  `OpenNLP <https://opennlp.apache.org/>`__
-  `NLP4J <https://emorynlp.github.io/nlp4j/>`__
-  `Word2vec in
   Java <https://deeplearning4j.org/docs/latest/deeplearning4j-nlp-word2vec>`__
-  `ReVerb <https://github.com/knowitall/reverb/>`__ Web-Scale Open
   Information Extraction
-  `OpenRegex <https://github.com/knowitall/openregex>`__ An efficient
   and flexible token-based regular expression language and engine.
-  `CogcompNLP <https://github.com/CogComp/cogcomp-nlp>`__ - Core
   libraries developed in the U of Illinois’ Cognitive Computation
   Group.
-  `MALLET <http://mallet.cs.umass.edu/>`__ - MAchine Learning for
   LanguagE Toolkit - package for statistical natural language
   processing, document classification, clustering, topic modeling,
   information extraction, and other machine learning applications to
   text.
-  `RDRPOSTagger <https://github.com/datquocnguyen/RDRPOSTagger>`__ - A
   robust POS tagging toolkit available (in both Java & Python) together
   with pre-trained models for 40+ languages.

Kotlin
~~~~~~

   Kotlin NLP 库

-  `Lingua <https://github.com/pemistahl/lingua/>`__ A language
   detection library for Kotlin and Java, suitable for long and short
   text alike
-  `Kotidgy <https://github.com/meiblorn/kotidgy>`__ — an index-based
   text data generator written in Kotlin

Scala
~~~~~

   Scala NLP 库

-  `Saul <https://github.com/CogComp/saul>`__ - Library for developing
   NLP systems, including built in modules like SRL, POS, etc.
-  `ATR4S <https://github.com/ispras/atr4s>`__ - Toolkit with
   state-of-the-art `automatic term
   recognition <https://en.wikipedia.org/wiki/Terminology_extraction>`__
   methods.
-  `tm <https://github.com/ispras/tm>`__ - Implementation of topic
   modeling based on regularized multilingual
   `PLSA <https://en.wikipedia.org/wiki/Probabilistic_latent_semantic_analysis>`__.
-  `word2vec-scala <https://github.com/Refefer/word2vec-scala>`__ -
   Scala interface to word2vec model; includes operations on vectors
   like word-distance and word-analogy.
-  `Epic <https://github.com/dlwh/epic>`__ - Epic is a high performance
   statistical parser written in Scala, along with a framework for
   building complex structured prediction models.

R
~

   R NLP 库

-  `text2vec <https://github.com/dselivanov/text2vec>`__ - Fast
   vectorization, topic modeling, distances and GloVe word embeddings in
   R.
-  `wordVectors <https://github.com/bmschmidt/wordVectors>`__ - An R
   package for creating and exploring word2vec and other word embedding
   models
-  `RMallet <https://github.com/mimno/RMallet>`__ - R package to
   interface with the Java machine learning tool MALLET
-  `dfr-browser <https://github.com/agoldst/dfr-browser>`__ - Creates d3
   visualizations for browsing topic models of text in a web browser.
-  `dfrtopics <https://github.com/agoldst/dfrtopics>`__ - R package for
   exploring topic models of text.
-  `sentiment_classifier <https://github.com/kevincobain2000/sentiment_classifier>`__
   - Sentiment Classification using Word Sense Disambiguation and
   WordNet Reader
-  `jProcessing <https://github.com/kevincobain2000/jProcessing>`__ -
   Japanese Natural Langauge Processing Libraries, with Japanese
   sentiment classification

Clojure
~~~~~~~

-  `Clojure-openNLP <https://github.com/dakrone/clojure-opennlp>`__ -
   Natural Language Processing in Clojure (opennlp)
-  `Infections-clj <https://github.com/r0man/inflections-clj>`__ -
   Rails-like inflection library for Clojure and ClojureScript
-  `postagga <https://github.com/fekr/postagga>`__ - A library to parse
   natural language in Clojure and ClojureScript

Ruby
~~~~

-  Kevin Dias’s `A collection of Natural Language Processing (NLP) Ruby
   libraries, tools and
   software <https://github.com/diasks2/ruby-nlp>`__
-  `Practical Natural Language Processing done in
   Ruby <https://github.com/arbox/nlp-with-ruby>`__

Rust
~~~~

-  `whatlang <https://github.com/greyblake/whatlang-rs>`__ —
   基于三元组的自然语言识别库
-  `snips-nlu-rs <https://github.com/snipsco/snips-nlu-rs>`__ -
   用于意图解析的生产就绪库

服务
----

NLP 作为具有更高级功能的 API，例如 NER，主题标记等

-  `Wit-ai <https://github.com/wit-ai/wit>`__ - 应用和设备的自然语言界面
-  `IBM Watson
   的自然语言理解 <https://github.com/watson-developer-cloud/natural-language-understanding-nodejs>`__
   - API 和 Github 演示
-  `亚马逊领悟 <https://aws.amazon.com/comprehend/>`__ - NLP 和 ML
   套件涵盖了最常见的任务，如 NER，标记和情感分析
-  `谷歌云自然语言 API <https://cloud.google.com/natural-language/>`__ -
   至少 9 种语言的语法分析，NER，情感分析和内容标记包括英语和中文
   (简体和繁体).
-  `平行点 <https://www.paralleldots.com/text-analysis-apis>`__ -
   高级文本分析 API 服务，从情感分析到意图分析
-  `Microsoft
   认知服务 <https://azure.microsoft.com/en-us/services/cognitive-services/text-analytics/>`__
-  `文字剃刀 <https://www.textrazor.com/>`__
-  `罗塞特 <https://www.rosette.com/>`__

注释工具
--------

-  `GATE <https://gate.ac.uk/overview.html>`__ - 通用架构和文本工程已有
   15 年历史，免费和开源
-  `Anafora <https://github.com/weitechen/anafora>`__ 是免费的开源，基于
   Web 的原始文本注释工具
-  `brat <https://brat.nlplab.org/>`__ - brat rapid annotation tool
   是一个用于协作文本注释的在线环境
-  `tagtog <https://www.tagtog.net/>`__, costs $
-  `prodigy <https://prodi.gy/>`__ 是一种由主动学习提供支持的注释工具,
   costs $
-  `LightTag <https://lighttag.io>`__ -
   为团队提供托管和管理的文本注释工具, costs $