In the last decade, research on language technology applications, such as machine translation (MT), information retrieval and extraction (also cross-linguistic), etc. has benefited from the significant advances obtained with the exploitation of increasingly sophisticated statistical approaches. To a large extent, this advancement has been achieved also by encompassing a host of subsidiary and increasingly more fine-grained linguistic distinctions at the syntactic and semantic levels. Thus, the NLP mainstream has headed towards the modeling of multilayered linguistic knowledge. To leap forward in terms of the quality of its output, machine translation and other technologies are taking advantage of enhanced capacities for deeper analysis of natural language and massive open online world knowledge that are now becoming available. The following initiatives can be mentioned as best practices, among others: LOGON MT system from-Norwegian-to-English which uses Minimal Recursion Semantics (MRS) and DELPH-IN deep HPSG grammar expertise for language transfer; Systems based on Abstract Meaning Representation (AMR); The ParGram parallel deep grammars and parsebanks covering several language families in the LFG formalism; The development of sophisticated syntactic and semantic models, sensitive to lexical semantics and semantic roles; Creation of high-quality parallel treebanks via model transfers (such as Prague Czech-English Dependency treebank); Creation of deep resources, such as English DeepBank, released in 2013; Creation of common tagsets and thus ‘universalizing’ linguistic resources, such as treebanks in Google, the HamleDT project, etc. In the long run, richer world knowledge will be available, even beyond the current Linked Open Data, with respect to larger datasets, richer semantics enhanced with world facts, and more dynamic conceptual knowledge representation. Concomitantly, the evolutive trend in Natural Language Processing shows a strong integration of the knowledge-poor language processing with the knowledge-rich one, supported by deep grammars and deep language resources. This workshop joins forces of the former Advanced Treebanking community, as represented by the 2012 LREC Workshop on Advanced Treebanking, with the new stream of projects aimed at high quality applications, most prominently - Machine Translation. The workshop invites papers on progress in the use of deep natural language processing and resources providing deep analyses for a range of applications including, but not limited to, machine translation.