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This paper deals with the entity extraction task (named entity recognition)of a text mining process that aims at unveiling non-trivial semanticstructures, such as relationships and interaction between entities orcommunities. In this paper we present a simple and efficient named entityextraction algorithm. The method, named PAMPO (PAttern Matching and POs taggingbased algorithm for NER), relies on flexible pattern matching, part-of-speechtagging and lexical-based rules. It was developed to process texts written inPortuguese, however it is potentially applicable to other languages as well.  We compare our approach with current alternatives that support Named EntityRecognition (NER) for content written in Portuguese. These are Alchemy, Zemantaand Rembrandt. Evaluation of the efficacy of the entity extraction method onseveral texts written in Portuguese indicates a considerable improvement on$recall$ and $F_1$ measures.

PAMPO: using pattern matching and pos-tagging for effective Named Entities recognition in Portuguese