Abstract
The size of massive knowledge graphs (KGs) and the lack of prior information regarding the schemas, ontologies and vocabularies they use frequently makes them hard to understand and visualize. Graph summarization techniques can help by abstracting details of the original graph to produce a reduced summary that can more easily be explored. Identifiers often carry latent information which could be used for classification of the entities they represent. Particularly, IRI namespaces can be used to classify RDF resources. Namespaces, used in some RDF serialization formats as a shortening mechanism for resource IRIs, have no role in the semantics of RDF. Nevertheless, there is often a hidden meaning behind the decision of grouping resources under a common prefix and assigning an alias to it. We improved on previous work on a namespace-based approach to KG summarization that classifies resources using their namespaces. Producing the summary graph is fast, light on computing resources and requires no previous domain knowledge. The summary graph can be used to analyze the namespace interdependencies of the original graph. We also present chilon, a tool for calculating namespace-based KG summaries. Namespaces are gathered from explicit declarations in the graph serialization, community contributions or resource IRI prefix analysis. We applied chilon to publicly available KGs, used it to generate interactive visualizations of the summaries, and discuss the results obtained.

Abstract
Languages are born, evolve and, eventually, die. During this evolution their spelling rules (and sometimes the syntactic and semantic ones) change, putting old documents out of use. In Portugal, a pair of political agreements with Brazil forced relevant changes on the way the Portuguese language is written. In this article we will detail these two Orthographic Agreements (one in the thirties and the other more recently, in the nineties), and the challenges present on the automatic migration of old documents spelling to their actual one. We will reveal Bigorna, a toolkit for the classification of language variants, their comparison and the conversion of texts in different language versions. These tools will be explained together with examples of migration issues. As Birgorna relies on a set of conversion rules we will also discuss how to infer conversion rules from a set of documents (texts with different ages). The document concludes with a brief evaluation on the conversion and classification tool results and their relevance in the current Portuguese language scenario.

Abstract
Text alignment is one of the main processes for obtaining parallel corpora. When aligning two versions of a book, results are often affected by unpaired sections - sections which only exist in one of the versions of the book. We developed Text : : Perfide : : BookSync, a Perl module which performs books synchronization (structural alignment based on section delimitation), provided they have been previously annotated by Text : : Perfide : : BookCleaner. We discuss the need for such a tool and several implementation decisions. The main functions are described, and examples of input and output are presented. Text : : Perfide : : PartialAlign is an extension of the partialAlign.py tool bundled with hunalign which proposes an alternative methods for splitting bitexts.