An index is a very good tool for finding information in a set of documents. So far, existent index tools in both the printed and digital newspaper versions are not sufficient to help users find information. Users must browse the entire newspaper or discover, after spending a considerable amount of energy, that the information is not available. We propose here to use state-of-the-art strategies for extracting named entities specifically for person names and, with an index of names, provide the user with an important tool to find names within newspaper pages. The state-of-the-art system considered uses the Golden Collection of the First and Second HAREM, a reference for Named Entity Recognition systems in Portuguese, as training and test sets respectively. Furthermore, we created a new training dataset from the newspaper’s articles. We processed 100 articles and managed to correctly find 87.0% of the names and their respective partial citations.