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Improving NLTK for Processing Portuguese

Authors João Ferreira, Hugo Gonçalo Oliveira , Ricardo Rodrigues

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Author Details

João Ferreira
  • Department of Informatics Engineering of the University of Coimbra, Portugal
Hugo Gonçalo Oliveira
  • Centre for Informatics and Systems of the University of Coimbra, Portugal
  • Department of Informatics Engineering of the University of Coimbra, Portugal
Ricardo Rodrigues
  • Centre for Informatics and Systems of the University of Coimbra, Portugal
  • College of Education of the Polytechnic Institute of Coimbra, Portugal

Funding

This work was funded by FCT’s INCoDe 2030 initiative, in the scope of the demonstration project AIA, "Apoio Inteligente a Empreendedores (Chatbots)". We also thank Fábio Lopes for his help with NER based on CRF.

Cite AsGet BibTex

João Ferreira, Hugo Gonçalo Oliveira, and Ricardo Rodrigues. Improving NLTK for Processing Portuguese. In 8th Symposium on Languages, Applications and Technologies (SLATE 2019). Open Access Series in Informatics (OASIcs), Volume 74, pp. 18:1-18:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)
https://doi.org/10.4230/OASIcs.SLATE.2019.18

Abstract

Python has a growing community of users, especially in the AI and ML fields. Yet, Computational Processing of Portuguese in this programming language is limited, in both available tools and results. This paper describes NLPyPort, a NLP pipeline in Python, primarily based on NLTK, and focused on Portuguese. It is mostly assembled from pre-existent resources or their adaptations, but improves over the performance of existing alternatives in Python, namely in the tasks of tokenization, PoS tagging, lemmatization and NER.

Subject Classification

ACM Subject Classification
  • Computing methodologies → Natural language processing
Keywords
  • NLP
  • Tokenization
  • PoS tagging
  • Lemmatization
  • Named Entity Recognition

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References

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