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|
%global _empty_manifest_terminate_build 0
Name: python-estnltk
Version: 1.7.1
Release: 1
Summary: Estnltk — open source tools for Estonian natural language processing
License: GPLv2
URL: https://github.com/estnltk/estnltk
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/6c/fc/4b3bd898e0d48cc8ca902ef27eb460188b0447d7f176cfddae40f5a17e46/estnltk-1.7.1.tar.gz
Requires: python3-estnltk-core
Requires: python3-regex
Requires: python3-crfsuite
Requires: python3-cached-property
Requires: python3-bs4
Requires: python3-html5lib
Requires: python3-lxml
Requires: python3-requests
Requires: python3-tqdm
Requires: python3-conllu
Requires: python3-pandas
Requires: python3-pyahocorasick
Requires: python3-networkx
Requires: python3-matplotlib
Requires: python3-ipython
Requires: python3-networkx
Requires: python3-matplotlib
Requires: python3-ipython
Requires: python3-networkx
Requires: python3-matplotlib
Requires: python3-ipython
Requires: python3-nltk
%description
EstNLTK provides common natural language processing functionality such as paragraph, sentence and word tokenization,
morphological analysis, named entity recognition, etc. for the Estonian language.
The project is funded by EKT ([Eesti Keeletehnoloogia Riiklik Programm](https://www.keeletehnoloogia.ee/)).
This package contains EstNLTK's basic linguistic analysis, system and database tools:
* `Text` class with the Estonian NLP pipeline;
* tokenization tools: word, sentence and paragraph tokenization; clause segmentation;
* morphology tools: morphological analysis and disambiguation, spelling correction, morphological synthesis and syllabification, HFST based analyser and GT converter;
* information extraction tools: addresses tagger, named entity recognizer, temporal expression tagger; tools for rule based and grammar based fact extraction;
* experimental taggers: verb chain detector, noun phrase chunker, adjective phrase tagger;
* syntactic analysis tools: preprocessing for syntactic analysis, VislCG3 and Maltparser based syntactic parsers;
* Estonian Wordnet and Collocation-Net;
* web taggers -- such as bert embeddings web tagger, stanza syntax web tagger and stanza ensemble syntax web tagger;
* corpus importing tools -- tools for importing data from large Estonian corpora, such as the Reference Corpus or the National Corpus of Estonia;
* system taggers -- regex tagger, disambiguator, atomizer, merge tagger etc;
* utils for downloading additional resources (e.g. model files required by taggers);
* Postgres database tools;
## Version 1.7
### Installation
EstNLTK is available for osx, windows-64, and linux-64, and for python versions 3.7 to 3.10.
You can install the latest version via PyPI:
```
pip install estnltk==1.7.1
```
Alternatively, you can install EstNLTK via [Anaconda](https://www.anaconda.com/download). Installation steps with conda:
1. [create a conda environment](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#creating-an-environment-with-commands) with python 3.8, for instance:
```
conda create -n py38 python=3.8
```
2. [activate the environment](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#activating-an-environment), for instance:
```
conda activate py38
```
3. install EstNLTK with the command:
```
conda install -c estnltk -c conda-forge estnltk=1.7.1
```
_Note_: for using some of the tools in estnltk, you also need to have Java installed in your system. We recommend using Oracle Java http://www.oracle.com/technetwork/java/javase/downloads/index.html, although alternatives such as OpenJDK (http://openjdk.java.net/) should also work.
### Using on Google Colab
You can install EstNLTK on [Google Colab](https://colab.research.google.com) environment via command:
```
!pip install estnltk==1.7.1
```
### Documentation
EstNLTK's tutorials come in the form of [jupyter notebooks](http://jupyter.org).
* [Starting point of tutorials](https://github.com/estnltk/estnltk/tree/main/tutorials)
Additional educational materials on EstNLTK are available on web pages of an NLP course taught at the University of Tartu:
* [https://github.com/d009/EstNLP](https://github.com/d009/EstNLP) (in Estonian)
Note: if you have trouble viewing jupyter notebooks in github (you get an error message _Sorry, something went wrong. Reload?_ at loading a notebook), then try to open notebooks with the help of [https://nbviewer.jupyter.org](https://nbviewer.jupyter.org)
### Source
The source of the last release is available at the [main branch](https://github.com/estnltk/estnltk/tree/main/estnltk).
Changelog is available [here](https://github.com/estnltk/estnltk/blob/main/CHANGELOG.md).
## Citation
In case you use EstNLTK in your work, please cite us as follows:
@InProceedings{laur-EtAl:2020:LREC,
author = {Laur, Sven and Orasmaa, Siim and Särg, Dage and Tammo, Paul},
title = {EstNLTK 1.6: Remastered Estonian NLP Pipeline},
booktitle = {Proceedings of The 12th Language Resources and Evaluation Conference},
month = {May},
year = {2020},
address = {Marseille, France},
publisher = {European Language Resources Association},
pages = {7154--7162},
url = {https://www.aclweb.org/anthology/2020.lrec-1.884}
%package -n python3-estnltk
Summary: Estnltk — open source tools for Estonian natural language processing
Provides: python-estnltk
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
BuildRequires: python3-cffi
BuildRequires: gcc
BuildRequires: gdb
%description -n python3-estnltk
EstNLTK provides common natural language processing functionality such as paragraph, sentence and word tokenization,
morphological analysis, named entity recognition, etc. for the Estonian language.
The project is funded by EKT ([Eesti Keeletehnoloogia Riiklik Programm](https://www.keeletehnoloogia.ee/)).
This package contains EstNLTK's basic linguistic analysis, system and database tools:
* `Text` class with the Estonian NLP pipeline;
* tokenization tools: word, sentence and paragraph tokenization; clause segmentation;
* morphology tools: morphological analysis and disambiguation, spelling correction, morphological synthesis and syllabification, HFST based analyser and GT converter;
* information extraction tools: addresses tagger, named entity recognizer, temporal expression tagger; tools for rule based and grammar based fact extraction;
* experimental taggers: verb chain detector, noun phrase chunker, adjective phrase tagger;
* syntactic analysis tools: preprocessing for syntactic analysis, VislCG3 and Maltparser based syntactic parsers;
* Estonian Wordnet and Collocation-Net;
* web taggers -- such as bert embeddings web tagger, stanza syntax web tagger and stanza ensemble syntax web tagger;
* corpus importing tools -- tools for importing data from large Estonian corpora, such as the Reference Corpus or the National Corpus of Estonia;
* system taggers -- regex tagger, disambiguator, atomizer, merge tagger etc;
* utils for downloading additional resources (e.g. model files required by taggers);
* Postgres database tools;
## Version 1.7
### Installation
EstNLTK is available for osx, windows-64, and linux-64, and for python versions 3.7 to 3.10.
You can install the latest version via PyPI:
```
pip install estnltk==1.7.1
```
Alternatively, you can install EstNLTK via [Anaconda](https://www.anaconda.com/download). Installation steps with conda:
1. [create a conda environment](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#creating-an-environment-with-commands) with python 3.8, for instance:
```
conda create -n py38 python=3.8
```
2. [activate the environment](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#activating-an-environment), for instance:
```
conda activate py38
```
3. install EstNLTK with the command:
```
conda install -c estnltk -c conda-forge estnltk=1.7.1
```
_Note_: for using some of the tools in estnltk, you also need to have Java installed in your system. We recommend using Oracle Java http://www.oracle.com/technetwork/java/javase/downloads/index.html, although alternatives such as OpenJDK (http://openjdk.java.net/) should also work.
### Using on Google Colab
You can install EstNLTK on [Google Colab](https://colab.research.google.com) environment via command:
```
!pip install estnltk==1.7.1
```
### Documentation
EstNLTK's tutorials come in the form of [jupyter notebooks](http://jupyter.org).
* [Starting point of tutorials](https://github.com/estnltk/estnltk/tree/main/tutorials)
Additional educational materials on EstNLTK are available on web pages of an NLP course taught at the University of Tartu:
* [https://github.com/d009/EstNLP](https://github.com/d009/EstNLP) (in Estonian)
Note: if you have trouble viewing jupyter notebooks in github (you get an error message _Sorry, something went wrong. Reload?_ at loading a notebook), then try to open notebooks with the help of [https://nbviewer.jupyter.org](https://nbviewer.jupyter.org)
### Source
The source of the last release is available at the [main branch](https://github.com/estnltk/estnltk/tree/main/estnltk).
Changelog is available [here](https://github.com/estnltk/estnltk/blob/main/CHANGELOG.md).
## Citation
In case you use EstNLTK in your work, please cite us as follows:
@InProceedings{laur-EtAl:2020:LREC,
author = {Laur, Sven and Orasmaa, Siim and Särg, Dage and Tammo, Paul},
title = {EstNLTK 1.6: Remastered Estonian NLP Pipeline},
booktitle = {Proceedings of The 12th Language Resources and Evaluation Conference},
month = {May},
year = {2020},
address = {Marseille, France},
publisher = {European Language Resources Association},
pages = {7154--7162},
url = {https://www.aclweb.org/anthology/2020.lrec-1.884}
%package help
Summary: Development documents and examples for estnltk
Provides: python3-estnltk-doc
%description help
EstNLTK provides common natural language processing functionality such as paragraph, sentence and word tokenization,
morphological analysis, named entity recognition, etc. for the Estonian language.
The project is funded by EKT ([Eesti Keeletehnoloogia Riiklik Programm](https://www.keeletehnoloogia.ee/)).
This package contains EstNLTK's basic linguistic analysis, system and database tools:
* `Text` class with the Estonian NLP pipeline;
* tokenization tools: word, sentence and paragraph tokenization; clause segmentation;
* morphology tools: morphological analysis and disambiguation, spelling correction, morphological synthesis and syllabification, HFST based analyser and GT converter;
* information extraction tools: addresses tagger, named entity recognizer, temporal expression tagger; tools for rule based and grammar based fact extraction;
* experimental taggers: verb chain detector, noun phrase chunker, adjective phrase tagger;
* syntactic analysis tools: preprocessing for syntactic analysis, VislCG3 and Maltparser based syntactic parsers;
* Estonian Wordnet and Collocation-Net;
* web taggers -- such as bert embeddings web tagger, stanza syntax web tagger and stanza ensemble syntax web tagger;
* corpus importing tools -- tools for importing data from large Estonian corpora, such as the Reference Corpus or the National Corpus of Estonia;
* system taggers -- regex tagger, disambiguator, atomizer, merge tagger etc;
* utils for downloading additional resources (e.g. model files required by taggers);
* Postgres database tools;
## Version 1.7
### Installation
EstNLTK is available for osx, windows-64, and linux-64, and for python versions 3.7 to 3.10.
You can install the latest version via PyPI:
```
pip install estnltk==1.7.1
```
Alternatively, you can install EstNLTK via [Anaconda](https://www.anaconda.com/download). Installation steps with conda:
1. [create a conda environment](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#creating-an-environment-with-commands) with python 3.8, for instance:
```
conda create -n py38 python=3.8
```
2. [activate the environment](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#activating-an-environment), for instance:
```
conda activate py38
```
3. install EstNLTK with the command:
```
conda install -c estnltk -c conda-forge estnltk=1.7.1
```
_Note_: for using some of the tools in estnltk, you also need to have Java installed in your system. We recommend using Oracle Java http://www.oracle.com/technetwork/java/javase/downloads/index.html, although alternatives such as OpenJDK (http://openjdk.java.net/) should also work.
### Using on Google Colab
You can install EstNLTK on [Google Colab](https://colab.research.google.com) environment via command:
```
!pip install estnltk==1.7.1
```
### Documentation
EstNLTK's tutorials come in the form of [jupyter notebooks](http://jupyter.org).
* [Starting point of tutorials](https://github.com/estnltk/estnltk/tree/main/tutorials)
Additional educational materials on EstNLTK are available on web pages of an NLP course taught at the University of Tartu:
* [https://github.com/d009/EstNLP](https://github.com/d009/EstNLP) (in Estonian)
Note: if you have trouble viewing jupyter notebooks in github (you get an error message _Sorry, something went wrong. Reload?_ at loading a notebook), then try to open notebooks with the help of [https://nbviewer.jupyter.org](https://nbviewer.jupyter.org)
### Source
The source of the last release is available at the [main branch](https://github.com/estnltk/estnltk/tree/main/estnltk).
Changelog is available [here](https://github.com/estnltk/estnltk/blob/main/CHANGELOG.md).
## Citation
In case you use EstNLTK in your work, please cite us as follows:
@InProceedings{laur-EtAl:2020:LREC,
author = {Laur, Sven and Orasmaa, Siim and Särg, Dage and Tammo, Paul},
title = {EstNLTK 1.6: Remastered Estonian NLP Pipeline},
booktitle = {Proceedings of The 12th Language Resources and Evaluation Conference},
month = {May},
year = {2020},
address = {Marseille, France},
publisher = {European Language Resources Association},
pages = {7154--7162},
url = {https://www.aclweb.org/anthology/2020.lrec-1.884}
%prep
%autosetup -n estnltk-1.7.1
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-estnltk -f filelist.lst
%dir %{python3_sitearch}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Wed May 10 2023 Python_Bot <Python_Bot@openeuler.org> - 1.7.1-1
- Package Spec generated
|
