The Conference on Computational Natural Language Learning (CoNLL) features a shared task, in which participants train and test their learning systems on the same data sets. In 2017, one of two tasks was devoted to learning dependency parsers for a large number of languages, in a realworld setting without any gold-standard annotation on input. All test sets followed a unified annotation scheme, namely that of Universal Dependencies. In this paper, we define the task and evaluation methodology, describe data preparation, report and analyze the main results, and provide a brief categorization of the different approaches of the participating systems.

Universal dependencies (UD) is a framework for morphosyntactic annotation of human language, which to date has been used to create treebanks for more than 100 languages. In this article, we outline the linguistic theory of the UD framework, which draws on a long tradition of typologically oriented grammatical theories. Grammatical relations between words are centrally used to explain how predicate–argument structures are encoded morphosyntactically in different languages while morphological features and part-of-speech classes give the properties of words. We argue that this theory is a good basis for cross-linguistically consistent annotation of typologically diverse languages in a way that supports computational natural language understanding as well as broader linguistic studies.

This perspective refl ects the developments in the fi eld of green biorefi ning in the last decade from an overall European perspective. It discusses selected main national grass biorefi nery activities and pilot facilities available in different European countries. An estimate of surplus grassland and potential impact on European economy is presented. A focus for future R&D work in that fi eld is recommended.

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Sweet sorghum juice (SSJ) was evaluated as fermentation substrate for the production of l-lactic acid. A thermophilic Bacillus coagulans isolate was selected for batch fermentations without the use of additional nutrients. The first batch of SSJ (Batch A) resulted on higher lactic acid concentration, yield and productivity with values of 78.75 g∙L−1, 0.78 g∙g−1 and 1.77 g∙L−1 h−1, respectively. Similar results were obtained when the process was transferred into the pilot scale (50 L), with corresponding values of 73 g∙L−1, 0.70 g∙g−1 and 1.47 g∙L−1 h−1. A complete downstream process scheme was developed in order to separate lactic acid from the fermentation components. Coarse and ultra-filtration were employed as preliminary separation steps. Mono- and bipolar electrodialysis, followed by chromatography and vacuum evaporation were subsequently carried out leading to a solution containing 905.8 g∙L−1 lactic acid, with an optical purity of 98.9%. The results of this study highlight the importance of the downstream process with respect to using SSJ for lactic acid production. The proposed downstream process constitutes a more environmentally benign approach to conventional precipitation methods.