https://github.com/ufal/udpipe

UDPipe: Trainable pipeline for tokenizing, tagging, lemmatizing and parsing Universal Treebanks and other CoNLL-U files
https://github.com/ufal/udpipe

Last synced: about 2 months ago
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UDPipe: Trainable pipeline for tokenizing, tagging, lemmatizing and parsing Universal Treebanks and other CoNLL-U files

• Host: GitHub
• URL: https://github.com/ufal/udpipe
• Owner: ufal
• License: mpl-2.0
• Created: 2016-01-29T15:51:21.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2023-12-14T21:47:17.000Z (6 months ago)
• Last Synced: 2024-04-17T06:42:34.775Z (about 2 months ago)
• Language: C++
• Size: 2.77 MB
• Stars: 352
• Watchers: 29
• Forks: 73
• Open Issues: 15
• Metadata Files:
  • Readme: README
  • Changelog: CHANGES.md
  • License: LICENSE
  • Authors: AUTHORS

Lists

• awesome-nlp - UDPipe - U 文件。主要用 C++ 編寫，為多語言NLP處理提供快速可靠的解決方案。 (多語言自然語言處理框架 / 回答問題與知識提取)
• awesome-nlp - UDPipe - U 文件。主要用 C++ 編寫，為多語言NLP處理提供快速可靠的解決方案。 (多語言自然語言處理框架 / 回答問題與知識提取)
• awesome-nlp - UDPipe - U 文件。主要用 C++ 編寫，為多語言NLP處理提供快速可靠的解決方案。 (多語言自然語言處理框架 / 回答問題與知識提取)
• awesome-nlp - UDPipe - U 文件。主要用 C++ 編寫，為多語言NLP處理提供快速可靠的解決方案。 (多語言自然語言處理框架 / 回答問題與知識提取)
• awesome-nlp - UDPipe - U 文件。主要用 C++ 編寫，為多語言NLP處理提供快速可靠的解決方案。 (多語言自然語言處理框架 / 回答問題與知識提取)

README

        
UDPipe 1

========

UDPipe is a trainable pipeline for tokenization, tagging, lemmatization and

dependency parsing of CoNLL-U files. UDPipe is language-agnostic and can be

trained given annotated data in CoNLL-U format

(http://universaldependencies.org/format.html). Trained models are provided for

nearly all UD treebanks (http://universaldependencies.org). UDPipe is available

as a binary for Linux/Windows/OS X, as a library for C++, Python, Perl, Java,

C#, and as a web service. Third-party R CRAN package

(https://CRAN.R-project.org/package=udpipe) also exists.

UDPipe is a free software distributed under the Mozilla Public License 2.0

(http://www.mozilla.org/MPL/2.0/) and the linguistic models are free for

non-commercial use and distributed under the CC BY-NC-SA

(http://creativecommons.org/licenses/by-nc-sa/4.0/) license, although for some

models the original data used to create the model may impose additional

licensing conditions. UDPipe is versioned using Semantic Versioning

(http://semver.org/).

Copyright 2017 by Institute of Formal and Applied Linguistics, Faculty of

Mathematics and Physics, Charles University, Czech Republic.

UDPipe website http://ufal.mff.cuni.cz/udpipe contains download links of both

the released packages and trained models, hosts documentation and offers online

web service.

UDPipe development repository http://github.com/ufal/udpipe is hosted on GitHub.

Third-party contribution: Instructions how to build UDPipe REST server as Docker

image is here: http://github.com/samisalkosuo/udpipe-rest-server-docker.

Instructions how to train UDPipe language models using a Docker image is also

there.