It has been thirteen years since the release of the current version (v3) of the Croatian National Corpus (HNK). In terms of synchronicity in corpus linguistics, that many years may be considered quite some time. The preparatory phase for the composition of the new version of HNK (v4) has been going already for several years and in this paper we touch on several issues of concern. Apart of regular corpus parameters, e.g. text sources, text genres, coverage of language varieties, time span, we also discuss about metadata and linguistic annotation schemata. One of important technical prerequisites was the development of CorpRepo, a custom corpus data management system and file system, which enable us to do sustainable long-term maintenance of the data, and to produce newer versions of corpus more easily and more often. The selection of IPR-cleared data entails some restrictions and we give several examples of that kind of textual sources, but also discuss possible weaknesses of such approach to data selection. Regarding the linguistic annotation, the important shift is the decision to abandon the MulText East morphosyntacting descriptions and use solutions recommended by UD-initiative.

This article presents the current outcomes of the CURLICAT CEF Telecom project, which aims to collect and deeply annotate a set of large corpora from selected domains. The CURLICAT corpus includes 7 monolingual corpora (Bulgarian, Croatian, Hungarian, Polish, Romanian, Slovak and Slovenian) containing selected samples from respective national corpora. These corpora are automatically tokenized, lemmatized and morphologically analysed and the named entities annotated. The annotations are uniformly provided for each language specific corpus while the common metadata schema is harmonised across the languages. Additionally, the corpora are annotated for IATE terms in all languages. The file format is CoNLL-U Plus format, containing the ten columns specific to the CoNLL-U format and three extra columns specific to our corpora as defined by Varádi et al. (2020). The CURLICAT corpora represent a rich and valuable source not just for training NMT models, but also for further studies and developments in machine learning, cross-lingual terminological data extraction and classification.

In the paper authors present the Croatian corpus of non-professional written language. Consisting of two subcorpora, i.e. the clinical subcorpus, consisting of written texts produced by speakers with various types of language disorders, and the healthy speakers subcorpus, as well as by the levels of its annotation, it offers an opportunity for different lines of research. The authors present the corpus structure, describe the sampling methodology, explain the levels of annotation, and give some very basic statistics. On the basis of data from the corpus, existing language technologies for Croatian are adapted in order to be implemented in a platform facilitating text production to speakers with language disorders. In this respect, several analyses of the corpus data and a basic evaluation of the developed technologies are presented.