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
Installing NLPyPort should be as simple as installing the requirments 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:
>>> pip install nltk==3.4.5If you installed NLTK and do not have downloaded the "Floresta" corpus, run the following commands:
>>> import nltk
>>> nltk.download('floresta')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.
Depending on the planed usage, the pipeline may be called in three different ways:
text = new_full_pipe( your_input_file )text = new_full_pipe( your_input_file , options = options )config_list = load_congif_to_list() # Pre-load the pipeline
text=new_full_pipe( your_input_file , options = options , config_list = config_list)"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
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.
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
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}}