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+%global _empty_manifest_terminate_build 0
+Name:		python-NLPyPort
+Version:	2.2.5
+Release:	1
+Summary:	Python NLP for Portuguese
+License:	cc0-1.0
+URL:		https://github.com/jdportugal/NLPyPort
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/b7/cb/27c653a479f649313c3d6da4dd88bbf6e92ed9f71f6cf64aa8cc177426c4/NLPyPort-2.2.5.tar.gz
+BuildArch:	noarch
+
+
+%description
+# NLPyPort
+
+
+The NLPy_Port is a pipeline assembled from the NLTK pipeline, adding and changing its elements for better processing the portuguese that were previouslly created for the NLPPort pipeline.
+It suports at the moment the taks of Tokenization, PoS Tagging , Lemmatization and Named Entity Recognition
+
+
+# Instalation
+Installing NLPyPort should be as simple as installing the requirements or installing the module via pip (pip install NLPyPort). However, some other configurations may be necessary. 
+
+If your NLTK version is above 3.4.5, install the version 3.4.5 by running:
+```bash
+>>> pip install nltk==3.4.5
+```
+
+If you installed NLTK and do not have downloaded the "Floresta" corpus, run the following commands:
+```bash
+>>> import nltk
+>>> nltk.download('floresta')
+```
+
+
+
+# Usage
+
+In order to simplify the usage of the NLPyPort pipeline, some structural changes were made. The “exemplo.py” file shows exemples os several use cases.
+
+## How to use the pipeline
+
+Depending on the planed usage, the pipeline may be called in three different ways:
+
+### 1  - Default 
+```python
+text = new_full_pipe( your_input_file )
+```
+
+
+### 2 - Optional arguments
+```python
+text = new_full_pipe( your_input_file , options = options )
+```
+
+
+### 3 - Optional arguments and pre-load pipeline
+```python
+config_list = load_congif_to_list()         # Pre-load the pipeline
+text=new_full_pipe( your_input_file , options = options , config_list = config_list)
+```
+
+
+## Available options
+
+"tokenizer" : True   -> Perform Tokenization
+
+"pos_tagger" : True -> Perform Pos Tagging
+
+"lemmatizer" : True -> Perform Lemmatization
+
+"entity_recognition" : True -> Perform NER
+
+"np_chunking" : True -> Perform NP Chunking
+
+"pre_load" : False -> Preload the pipeline, needs the additional argument “config_list”
+
+"string_or_array" : True -> Set input as being an array or a string
+
+
+## Returned text
+
+In case of success, the pipeline will return an object of the “Text” class. The properties of this are as follow:
+    text.tokens
+    text.pos_tags
+    text.lemas
+    text.entities
+    text.np_tags
+
+Additionally, there is a method to return the pipeline in the CoNNL Format:
+    text.print_conll()
+
+To separate lines , at the end of each line the additional token EOS is added.
+
+
+# Credits
+
+
+Tokenizer and Lemmatizer resource files - Rodrigues, Ricardo, Hugo Gonçalo Oliveira, and Paulo Gomes. "NLPPort: A Pipeline for Portuguese NLP (Short Paper)." 7th Symposium on Languages, Applications and Technologies (SLATE 2018). Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik, 2018.
+
+Lemmatizer design -  Rodrigues, Ricardo, Hugo Gonçalo Oliveira, and Paulo Gomes. "LemPORT: a high-accuracy cross-platform lemmatizer for portuguese." 3rd Symposium on Languages, Applications and Technologies. Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik, 2014.
+
+PoS trainer (adapted from) - https://github.com/fmaruki/Nltk-Tagger-Portuguese
+
+Named Entity Recognition  
+    CRF suite - Naoaki Okazaki http://www.chokkan.org/software/crfsuite/
+    sklearn-crfsuite wrapper - https://github.com/TeamHG-Memex/sklearn-crfsuite
+
+Corpus
+Corpus for PoS tagging training
+    MacMorpho - http://nilc.icmc.usp.br/macmorpho/ 
+    Floresta Sintá(c)tica - https://www.linguateca.pt/Floresta/corpus.html
+    
+    
+
+# Citations
+
+To cite and give credits to the pipeline please use the following BibText reference:
+
+@inproceedings{ferreira_etal:slate2019,
+    Author = {João Ferreira and Hugo {Gonçalo~Oliveira} and Ricardo Rodrigues},
+    Booktitle = {Symposium on Languages, Applications and Technologies (SLATE 2019)},
+    Month = {June},
+    Note = {In press},
+    Title = {Improving {NLTK} for Processing {P}ortuguese},
+    Year = {2019}}
+
+%package -n python3-NLPyPort
+Summary:	Python NLP for Portuguese
+Provides:	python-NLPyPort
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-NLPyPort
+# NLPyPort
+
+
+The NLPy_Port is a pipeline assembled from the NLTK pipeline, adding and changing its elements for better processing the portuguese that were previouslly created for the NLPPort pipeline.
+It suports at the moment the taks of Tokenization, PoS Tagging , Lemmatization and Named Entity Recognition
+
+
+# Instalation
+Installing NLPyPort should be as simple as installing the requirements or installing the module via pip (pip install NLPyPort). However, some other configurations may be necessary. 
+
+If your NLTK version is above 3.4.5, install the version 3.4.5 by running:
+```bash
+>>> pip install nltk==3.4.5
+```
+
+If you installed NLTK and do not have downloaded the "Floresta" corpus, run the following commands:
+```bash
+>>> import nltk
+>>> nltk.download('floresta')
+```
+
+
+
+# Usage
+
+In order to simplify the usage of the NLPyPort pipeline, some structural changes were made. The “exemplo.py” file shows exemples os several use cases.
+
+## How to use the pipeline
+
+Depending on the planed usage, the pipeline may be called in three different ways:
+
+### 1  - Default 
+```python
+text = new_full_pipe( your_input_file )
+```
+
+
+### 2 - Optional arguments
+```python
+text = new_full_pipe( your_input_file , options = options )
+```
+
+
+### 3 - Optional arguments and pre-load pipeline
+```python
+config_list = load_congif_to_list()         # Pre-load the pipeline
+text=new_full_pipe( your_input_file , options = options , config_list = config_list)
+```
+
+
+## Available options
+
+"tokenizer" : True   -> Perform Tokenization
+
+"pos_tagger" : True -> Perform Pos Tagging
+
+"lemmatizer" : True -> Perform Lemmatization
+
+"entity_recognition" : True -> Perform NER
+
+"np_chunking" : True -> Perform NP Chunking
+
+"pre_load" : False -> Preload the pipeline, needs the additional argument “config_list”
+
+"string_or_array" : True -> Set input as being an array or a string
+
+
+## Returned text
+
+In case of success, the pipeline will return an object of the “Text” class. The properties of this are as follow:
+    text.tokens
+    text.pos_tags
+    text.lemas
+    text.entities
+    text.np_tags
+
+Additionally, there is a method to return the pipeline in the CoNNL Format:
+    text.print_conll()
+
+To separate lines , at the end of each line the additional token EOS is added.
+
+
+# Credits
+
+
+Tokenizer and Lemmatizer resource files - Rodrigues, Ricardo, Hugo Gonçalo Oliveira, and Paulo Gomes. "NLPPort: A Pipeline for Portuguese NLP (Short Paper)." 7th Symposium on Languages, Applications and Technologies (SLATE 2018). Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik, 2018.
+
+Lemmatizer design -  Rodrigues, Ricardo, Hugo Gonçalo Oliveira, and Paulo Gomes. "LemPORT: a high-accuracy cross-platform lemmatizer for portuguese." 3rd Symposium on Languages, Applications and Technologies. Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik, 2014.
+
+PoS trainer (adapted from) - https://github.com/fmaruki/Nltk-Tagger-Portuguese
+
+Named Entity Recognition  
+    CRF suite - Naoaki Okazaki http://www.chokkan.org/software/crfsuite/
+    sklearn-crfsuite wrapper - https://github.com/TeamHG-Memex/sklearn-crfsuite
+
+Corpus
+Corpus for PoS tagging training
+    MacMorpho - http://nilc.icmc.usp.br/macmorpho/ 
+    Floresta Sintá(c)tica - https://www.linguateca.pt/Floresta/corpus.html
+    
+    
+
+# Citations
+
+To cite and give credits to the pipeline please use the following BibText reference:
+
+@inproceedings{ferreira_etal:slate2019,
+    Author = {João Ferreira and Hugo {Gonçalo~Oliveira} and Ricardo Rodrigues},
+    Booktitle = {Symposium on Languages, Applications and Technologies (SLATE 2019)},
+    Month = {June},
+    Note = {In press},
+    Title = {Improving {NLTK} for Processing {P}ortuguese},
+    Year = {2019}}
+
+%package help
+Summary:	Development documents and examples for NLPyPort
+Provides:	python3-NLPyPort-doc
+%description help
+# NLPyPort
+
+
+The NLPy_Port is a pipeline assembled from the NLTK pipeline, adding and changing its elements for better processing the portuguese that were previouslly created for the NLPPort pipeline.
+It suports at the moment the taks of Tokenization, PoS Tagging , Lemmatization and Named Entity Recognition
+
+
+# Instalation
+Installing NLPyPort should be as simple as installing the requirements or installing the module via pip (pip install NLPyPort). However, some other configurations may be necessary. 
+
+If your NLTK version is above 3.4.5, install the version 3.4.5 by running:
+```bash
+>>> pip install nltk==3.4.5
+```
+
+If you installed NLTK and do not have downloaded the "Floresta" corpus, run the following commands:
+```bash
+>>> import nltk
+>>> nltk.download('floresta')
+```
+
+
+
+# Usage
+
+In order to simplify the usage of the NLPyPort pipeline, some structural changes were made. The “exemplo.py” file shows exemples os several use cases.
+
+## How to use the pipeline
+
+Depending on the planed usage, the pipeline may be called in three different ways:
+
+### 1  - Default 
+```python
+text = new_full_pipe( your_input_file )
+```
+
+
+### 2 - Optional arguments
+```python
+text = new_full_pipe( your_input_file , options = options )
+```
+
+
+### 3 - Optional arguments and pre-load pipeline
+```python
+config_list = load_congif_to_list()         # Pre-load the pipeline
+text=new_full_pipe( your_input_file , options = options , config_list = config_list)
+```
+
+
+## Available options
+
+"tokenizer" : True   -> Perform Tokenization
+
+"pos_tagger" : True -> Perform Pos Tagging
+
+"lemmatizer" : True -> Perform Lemmatization
+
+"entity_recognition" : True -> Perform NER
+
+"np_chunking" : True -> Perform NP Chunking
+
+"pre_load" : False -> Preload the pipeline, needs the additional argument “config_list”
+
+"string_or_array" : True -> Set input as being an array or a string
+
+
+## Returned text
+
+In case of success, the pipeline will return an object of the “Text” class. The properties of this are as follow:
+    text.tokens
+    text.pos_tags
+    text.lemas
+    text.entities
+    text.np_tags
+
+Additionally, there is a method to return the pipeline in the CoNNL Format:
+    text.print_conll()
+
+To separate lines , at the end of each line the additional token EOS is added.
+
+
+# Credits
+
+
+Tokenizer and Lemmatizer resource files - Rodrigues, Ricardo, Hugo Gonçalo Oliveira, and Paulo Gomes. "NLPPort: A Pipeline for Portuguese NLP (Short Paper)." 7th Symposium on Languages, Applications and Technologies (SLATE 2018). Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik, 2018.
+
+Lemmatizer design -  Rodrigues, Ricardo, Hugo Gonçalo Oliveira, and Paulo Gomes. "LemPORT: a high-accuracy cross-platform lemmatizer for portuguese." 3rd Symposium on Languages, Applications and Technologies. Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik, 2014.
+
+PoS trainer (adapted from) - https://github.com/fmaruki/Nltk-Tagger-Portuguese
+
+Named Entity Recognition  
+    CRF suite - Naoaki Okazaki http://www.chokkan.org/software/crfsuite/
+    sklearn-crfsuite wrapper - https://github.com/TeamHG-Memex/sklearn-crfsuite
+
+Corpus
+Corpus for PoS tagging training
+    MacMorpho - http://nilc.icmc.usp.br/macmorpho/ 
+    Floresta Sintá(c)tica - https://www.linguateca.pt/Floresta/corpus.html
+    
+    
+
+# Citations
+
+To cite and give credits to the pipeline please use the following BibText reference:
+
+@inproceedings{ferreira_etal:slate2019,
+    Author = {João Ferreira and Hugo {Gonçalo~Oliveira} and Ricardo Rodrigues},
+    Booktitle = {Symposium on Languages, Applications and Technologies (SLATE 2019)},
+    Month = {June},
+    Note = {In press},
+    Title = {Improving {NLTK} for Processing {P}ortuguese},
+    Year = {2019}}
+
+%prep
+%autosetup -n NLPyPort-2.2.5
+
+%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-NLPyPort -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Wed May 31 2023 Python_Bot <Python_Bot@openeuler.org> - 2.2.5-1
+- Package Spec generated