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The Croatian-English parallel corpus MaCoCu-hr-en 1.0 was built by crawling the ".hr" internet top-level domain in 2021, extending the crawl dynamically to other domains as well. All the crawling process was carried out by the MaCoCu crawler (https://github.com/macocu/MaCoCu-crawler). Websites containing documents in both target languages were identified and processed using the tool Bitextor (https://github.com/bitextor/bitextor). Considerable efforts were devoted into cleaning the extracted text to provide a high-quality parallel corpus. This was achieved by removing boilerplate and near-duplicated paragraphs and documents that are not in one of the targeted languages. Document and segment alignment as implemented in Bitextor were carried out, and BicleanerAI (https://github.com/bitextor/bicleaner-ai) and Bifixer (https://github.com/bitextor/bifixer) were used for fixing, cleaning, and deduplicating the final version of the corpus. While the TXT format consists solely of pairs of source and target segments (one or several sentences), each segment pair in the TMX format is accompanied by the following metadata: - source and target document URL; - quality score as provided by the tool BicleanerAI; - translation direction identification: the source segment in each segment pair was identified by using a probabilistic model; - personal information identification (“biroamer-entities”): segments containing personal information are flagged, so final users of the corpus can decide whether to use these segments; - language variants: the language variant of English (British or American) was identified for every segment pair on document and domain level. Notice and take down: Should you consider that our data contains material that is owned by you and should therefore not be reproduced here, please: (1) Clearly identify yourself, with detailed contact data such as an address, telephone number or email address at which you can be contacted. (2) Clearly identify the copyrighted work claimed to be infringed. (3) Clearly identify the material that is claimed to be infringing and information reasonably sufficient in order to allow us to locate the material. (4) Please write to the contact person for this resource whose email is available in the full item record. We will comply with legitimate requests by removing the affected sources from the next release of the corpus. This action has received funding from the European Union's Connecting Europe Facility 2014-2020 - CEF Telecom, under Grant Agreement No. INEA/CEF/ICT/A2020/2278341. This communication reflects only the author’s view. The Agency is not responsible for any use that may be made of the information it contains.

The ParlaSpeech-HR dataset is built from parliamentary proceedings available in the Croatian part of the ParlaMint corpus and the parliamentary recordings available from the Croatian Parliament's YouTube channel. The corpus consists of segments 8-20 seconds in length. There are two transcripts available: the original one, and the one normalised via a simple rule-based normaliser. Each of the transcripts contains word-level alignments to the recordings. Each segment has a reference to the ParlaMint 2.1 corpus (http://hdl.handle.net/11356/1432) via utterance IDs. If a segment is based on a single utterance, speaker information for that segment is available as well. There is speaker information available for 381,849 segments, i.e., 95% of all segments. Speaker information consists of all the speaker information available from the ParlaMint 2.1 corpus (name, party, gender, age, status, role). There are all together 309 speakers in the dataset. The dataset is divided into a training, a development, and a testing subset. Development data consist of 500 segments coming from the 5 most frequent speakers, with the goal of not losing speaker variety on dev data. Test data consist of 513 segments that come from 3 male (258 segments) and 3 female speakers (255 segments). There are no segments coming from the 6 test speakers in the two remaining subsets. The 22,076 instances not having speaker information are not assigned to any of the three subsets. The remaining 380,836 instances form the training set.

The Croatian web corpus MaCoCu-hr 1.0 was built by crawling the ".hr" internet top-level domain in 2021, extending the crawl dynamically to other domains as well. The crawler is available at https://github.com/macocu/MaCoCu-crawler. Considerable efforts were devoted into cleaning the extracted text to provide a high-quality web corpus. This was achieved by removing boilerplate (https://corpus.tools/wiki/Justext) and near-duplicated paragraphs (https://corpus.tools/wiki/Onion), discarding very short texts as well as texts that are not in the target language. Furthermore, samples from the largest 1,500 domains were manually checked and bad domains, such as machine-translated domains, were removed. The dataset is characterized by extensive metadata which allows filtering the dataset based on text quality and other criteria (https://github.com/bitextor/monotextor), making the corpus highly useful for corpus linguistics studies, as well as for training language models and other language technologies. In the XML format, each document is accompanied by the following metadata: title, crawl date, url, domain, file type of the original document, distribution of languages inside the document, and a fluency score based on a language model. The text of each document is divided into paragraphs that are accompanied by metadata on the information whether a paragraph is a heading or not, metadata on the paragraph quality and fluency, the automatically identified language of the text in the paragraph, and information whether the paragraph contains sensitive information (identified via the Biroamer tool - https://github.com/bitextor/biroamer). The TSV format delivers sentence-level data, and contains the following metadata: sentence URL, paragraph and sentence ID within the document, a simhash and a quality score, which allow filtering out near-duplicate sentences (all sentences with the same simhash can be deleted, except for the one with the highest quality score), the language of the sentence, information on sentence fluency, and information whether the sentence contains personal or sensitive information (identified via the Biroamer sensitive data and named entity recognizer). Notice and take down: Should you consider that our data contains material that is owned by you and should therefore not be reproduced here, please: (1) Clearly identify yourself, with detailed contact data such as an address, telephone number or email address at which you can be contacted. (2) Clearly identify the copyrighted work claimed to be infringed. (3) Clearly identify the material that is claimed to be infringing and information reasonably sufficient in order to allow us to locate the material. (4) Please write to the contact person for this resource whose email is available in the full item record. We will comply with legitimate requests by removing the affected sources from the next release of the corpus. This action has received funding from the European Union's Connecting Europe Facility 2014-2020 - CEF Telecom, under Grant Agreement No. INEA/CEF/ICT/A2020/2278341. This communication reflects only the author’s view. The Agency is not responsible for any use that may be made of the information it contains.

Skripta za kolegij Kiparstvo 2 na Diplomskom studiju Odsjeka kiparstvo Umjetničke akademije u Splitu nastavlja se na skriptu za kolegij iz prethodnog semestra, Kiparstvo 1. Petnaest nastavnih jedinica nižu se slijedom sukladnim realnoj kiparskoj praksi, što predstavlja važno iskustvo za studente, osobito u kolegiju Kiparstvo 2 koji nastavno na prethodni kolegij omogućuje studentima daljnje razvijanje znanja i iskustva. Mogućnost percepcije i artikulacije novih sadržaja je jedan od najvažnijih aspekata razvoja procesa autorskog rada. Naglasak je na njegovoj otvorenosti i unaprjeđivanju, kao nadogradnji znanja iz prethodnog semestra. Kroz čitavu skriptu se utvrđuje osnovna struktura stvaralačkog procesa, no sada na zahtjevnijoj razini. Pažnja posvećena likovnom jeziku, kao temeljnom i objedinjujućem aspektu rada, u ovom semestru je dodatno naglašena i prezentirana nizom odabranih vizualnih primjera, kao i primjera citata autora koji se mogu tumačiti kao temelji izjave o radu. Skripta olakšava studentima ostvarivanje očekivanih ishoda učenja, odnosno osvješćivanje potpunog procesa realizacije suvremene autorske skulpture, od osmišljavanja ideje do izvedbe rada i promišljanja njegova postava u prostoru. The script for the course Sculpture 2 at the Graduate Study of the Department of Sculpture of the Art Academy in Split continues on the script for the course Sculpture 1 from the previous semester. Fifteen teaching units are arranged in sequences consistent with real sculptural practice. The possibility of perception and articulation of new content is one of the most important aspects of the development of the author's work process. The emphasis is on its openness and improvement, as an upgrade of knowledge from the previous semester. Throughout the script, the basic structure of the creative process is determined, but now at a more demanding level. The attention paid to the language of art, as a fundamental and unifying aspect of the work, this semester is further emphasized and presented by a series of selected visual examples, as well as examples of quotations from authors that can be interpreted as the basis of the artist’s statement. The script makes it easier for students to achieve the expected learning outcomes, i.e. awareness of the full process of realization of contemporary author's sculpture, from conceiving an idea to performing the work, and thinking about its layout in exhibition space.

The dataset of user comments provided for research purposes for the EMBEDDIA, a Horizon 2020 project, extracted from the database of user comments from the 24sata.hr news portal. The 24sata.hr is the largest-circulation daily newspaper in Croatia, reaching on average 2 million readers daily. The dataset provides the comments metadata including the link to the relevant article, the ID of the comment author (anonymized), and timestamp. The comments are also labelled if they are blocked by human moderators. Description of the Datasets. The 24sata dataset consists of 11 columns and 21548192 rows. Each row represents one user comment on the 24sata news portal. Comments are added by registered users below the published news article. Columns: 'comment_id' - The internal id of the comment. Unique for each row. 'user_id' - The internal id of the user writing the comment. Unique for each user. '0' for all blocked comments. 'content' - The content (text) of the user comment. 'site' - The site the comment came from. 'reply_to_id' - The 'comment_id' of the parent comment - if this comment was intended as a reply. 'created_date' - The date the comment was created. 'last_change' - The date the comment was last edited. 'article_id' - A public id of the article where this comment was posted. The article itself can be accessed by appending article_id to the site. So an article with article_id 614684 and site 'www.24sata.hr' can be found on 'www.24sata.hr/a-614684'. (note the added 'a-' before the article name) 'infringed_on_rule' - If the user has infringed on rules with this comment, id of the rule is given. The description of the rules is given below. 'like_counts' - A number of times other users have voted in favour of this comment, similar to the Like button. 'dislike_counts' - A number of times other users have voted against this comment, opposite of the Like button.

The model for morphosyntactic annotation of standard Croatian was built with the CLASSLA-StanfordNLP tool (https://github.com/clarinsi/classla-stanfordnlp) by training on the hr500k training corpus (http://hdl.handle.net/11356/1183) and using the CLARIN.SI-embed.hr word embeddings (http://hdl.handle.net/11356/1205). The model produces simultaneously UPOS, FEATS and XPOS (MULTEXT-East) labels. The estimated F1 of the XPOS annotations is ~94.1. The difference to the previous version of the model is that the pre-trained embeddings are limited to 250 thousand entries and adapted to the new code base.

The 24sata news portal consists of a portal with daily news and several smaller portals covering news from specific topics, such as automotive news, health, culinary content, and lifestyle advice. The dataset contains over 650,000 articles in Croatian from 2007 to 2019, as well as assigned tags. Description of the Dataset The dataset consists of 11 columns and 657806 rows. Each row represents a single news article published on the 24sata news portals. Besides the 'www.24sata.hr', the biggest news portal, articles from other niche portals affiliated with 24sata are also included. Columns: 'article_id' - Public id of the article on the new site. The article can be accessed by concatenating the site URL and article_id. For example, to access the article with article_id 614684, you can access it on 'www.24sata.hr/--614684'. This id is, by itself, not unique across the dataset - articles from different portals can share the same article_id. 'site' - The location of the portals where the article came from. There are eight different portals covering topics of daily news, to the more focused portals about automotive technologies and trends, health and wellness, culinary trends and recipes, or lifestyle advices. 'title' - The title of the news article. 'lead' - Lead text, a short introduction to the content of an article. Can be empty. 'content' - The content of the news article, contains the bulk of the text. Can be empty if the whole article could fit in the lead text. 'tags' - Tags, zero or more, separated with a '|' character. Article tags are chosen by the author of the article. 'section' - The main section of the news portal where the article was posted (does not need to be set). The most frequent section is 'Vijesti' (News). 'subsection' - The subsection of the section where the article was posted (does not need to be set). Each section can have multiple subsections. 'authors' - Article authors, zero or more, separated with a '|' character. The author does not need to sign the article if he chooses not to so this can be empty. 'published_from' - A date when this article appeared on the portal. Journalists can write the article in advance and pick a future date and time when it will appear on the site. Due to this strategy, the 'published_from' can be much later than the 'date_created'. 'date_created' - A date when this article was originally written. For all articles published before 2nd Feb 2010 the 'date_created' is set to 2nd Feb 2010 - this is the date when the portal was redesigned and the database with news articles recreated.

The corpus consists of texts collected from the most popular (based on the Reuters Institute Digital News Report for 2018, retrieved from http://www.digitalnewsreport.org in April, 2019) news portals in Croatia in the period from 2014 to 2018: Direktno, Dnevno, Net Hr, Hrt, Index_Hr, Jutarnji, Novilist, Rtl, SlobodnaDalmacija, Večernji, Tportal, Dnevnik. Web browsing and web crawling were used to select and store the texts with their useful HTML information (publication date of the article, its URL, and title). The linguistic processing of the corpus was performed with the CLASSLA package (https://pypi.org/project/classla/) on the levels of tokenization, sentence splitting, morphosyntactic tagging, lemmatization, dependency parsing and named entity recognition. This corpus is a linguistically-processed version of the original corpus published at https://repository.pfri.uniri.hr/islandora/object/pfri%3A2156 and is distributed in the CoNLL-U format (https://universaldependencies.org/format.html).

Sadržaj skripte dosljedno prati nastavni program te je koncipiran je u četiri faze i u petnaest nastavnih jedinica koje su u skripti opširno elaborirane objašnjenjima i primjerima. Kroz nijh student prolazi kroz sve etape konceptualizacije, realizacije i predstavljanja kiparskog djela, u čemu mu skripta služi kao temeljna literatura. Skripta objašnjava cilj i zadatak svake nastavne jedinice, elaborirajući temu kroz niz odabranih primjera umjetničkih djela hrvatskih i inozemnih kipara. Putem ovih primjera dodatno se razlažu umjetnički i tehnološki problemi s kojima se sreću studenti u svome radu: pojašnjavaju se različiti tipovi umjetničkih tema u rasponu od klasičnih tema do konceptualnih i autoreferencijalnih, načini njihove likovne interpretacije, odnos kiparskog medija prema kategorijama prostora i vremena, različite vrste umjetničke motivacije pri izboru teme, različita konotacijska značenja pojedinih materijala, aspekti izvedbe u pojedinim materijalima i slično. Pomoću skripte student može lakše pratiti sadržaje kolegija te se na nju osloniti pri promišljanju i planiranju vlastitog rada, razvoju individualnog stila i percepciji vlastite autorske pozicije s nesputanim tretmanom ideja i jasnom interpretacijom koncepata. The content of the script consistently follows the curriculum. It is conceived in four phases and in fifteen teaching units, which are extensively elaborated in the script with explanations and examples. Through them, the student goes through all stages of conceptualization, realization and presentation of a sculptural work, in which the script serves as the basic literature. The script explains the goal and task of each teaching unit, elaborating the topic through a series of selected examples of works of art by Croatian and foreign sculptors. These examples further explain the artistic and technological problems that students face in their work: they explain different types of artistic themes ranging from classical to conceptual and self-referential, ways of their artistic interpretation, the relationship of sculpture to categories of space and time, different types of artistic motivation in choosing a topic, different connotational meanings of certain materials, aspects of performance in certain materials etc. With the help of the script, the students can more easily follow the contents of the course and rely on it when thinking and planning their own work, developing individual style and perception of their own position with unfettered treatment of ideas and clear interpretation of concepts.

Croatian Web Dictionary – Mrežnik is a free, corpus-based, born-digital, monolingual, easily searchable, hypertext, normative online dictionary of the Croatian standard language. It consists of three modules: for adult native speakers of Croatian, schoolchildren, and non-native speakers of Croatian. It is the central meeting point of the existing language resources of the Institute of Croatian Language and Linguistics, but also of the language resources created within the project. From 1st March 2017 to 31st August 2021 the work on Mrežnik has been financed by the Croatian Science Foundation.