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