1081 Open source projects that are alternatives of or similar to Weixin_public_corpus

🚁 保险行业语料库，聊天机器人

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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.

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NLTK Data

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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 proces…

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Jcseg is a light weight NLP framework developed with Java. Provide CJK and English segmentation based on MMSEG algorithm, With also keywords extraction, key sentence extraction, summary extraction implemented based on TEXTRANK algorithm. Jcseg had a build-in http server and search modules for the latest lucene,solr,elasticsearch

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Cornell NLVR and NLVR2 are natural language grounding datasets. Each example shows a visual input and a sentence describing it, and is annotated with the truth-value of the sentence.

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).

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CogComp's Natural Language Processing libraries and Demos:

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💫 Industrial-strength Natural Language Processing (NLP) in Python