With the CINTIL-International Corpus of Portuguese, an ongoing corpus annotated with fully flegded grammatical representation, sentences get not only a high level of lexical, morphological and syntactic annotation but also a semantic analysis that prepares the data to a manual specification step and thus opens the way for a number of tools and resources for which there is a great research focus at the present. This paper reports on the construction of a propbank that builds on CINTIL-DeepGramBank, with nearly 10 thousand sentences, on the basis of a deep linguistic grammar and on the process and the linguistic criteria guiding that construction, which makes possible to obtain a complete PropBank with both syntactic and semantic levels of linguistic annotation. Taking into account this and the promising scores presented in this study for inter-annotator agreement, CINTIL-PropBank presents itself as a great resource to train a semantic role labeller, one of our goals with this project.

Corpora of sentences annotated with grammatical information have been deployed by extending the basic lexical and morphological data with increasingly complex information, such as phrase constituency, syntactic functions, semantic roles, etc. As these corpora grow in size and the linguistic information to be encoded reaches higher levels of sophistication, the utilization of annotation tools and, above all, supporting computational grammars appear no longer as a matter of convenience but of necessity. In this paper, we report on the design features, the development conditions and the methodological options of a deep linguistic databank, the CINTIL DeepGramBank. In this corpus, sentences are annotated with fully fledged linguistically informed grammatical representations that are produced by a deep linguistic processing grammar, thus consistently integrating morphological, syntactic and semantic information. We also report on how such corpus permits to straightforwardly obtain a whole range of past generation annotated corpora (POS, NER and morphology), current generation treebanks (constituency treebanks, dependency banks, propbanks) and next generation databanks (logical form banks) simply by means of a very residual selection/extraction effort to get the appropriate ""views"" exposing the relevant layers of information.