Shallow Processing of Portuguese: From Sentence Chunking to Nominal Lemmatization

This dissertation proposes a set of procedures for the computational processing of Portuguese. Five tasks are covered: Sentence Segmentation, Tokenization, Part-of-Speech Tagging, Nominal Featurization and Nominal Lemmatization. These are some of the initial steps producing linguistic information Ñ such as POS categories or lemmas Ñ that is important to most subsequent processing (e.g. syntactic and semantic analysis). I follow a shallow processing approach, where linguistic information is associated to text based on local information (i.e. using the word itself or perhaps a limited window of context containing just a few words). I begin by identifying and describing the key problems raised by each task, with special focus on the problems that are speci?c to Portuguese. After an overview of existing approaches and tools, I describe the solutions I followed to the issues raised previously. I then report on my implementation of these solutions, which are found either to yield state-of-the-art performance or, in some cases, to advance the state-of-the-art. The major result of this dissertation is thus threefold: A description of the problems found in NLP of Portuguese, a set of algorithms and the corresponding tools to tackle those problems, together with their evaluation result