%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 - 2.2.5-1 - Package Spec generated