Titles of courses possibly relevant to the Digital Humanities for 2017-2018, manually gathered from course catalogues of most Czech state colleges, including the names of the teachers, department and school names, and the school-unique course IDs. All this information was publicly available in the individual course catalogues accessed from the official websites of the individual colleges.
The aim of the course is to introduce digital humanities and to describe various aspects of digital content processing.
The course consists of 10 lessons with video material and a PowerPoint presentation with the same content.
Every lesson contains a practical session – either a Jupyter Notebook to work in Python or a text file with a short description of the task. Most of the practical tasks consist of running the programme and analyse the results.
Although the course does not focus on programming, the code can be reused easily in individual projects.
Some experience in running Python code is desirable but not required.
The data set includes training, development and test data from the shared tasks on pronoun-focused machine translation and cross-lingual pronoun prediction from the EMNLP 2015 workshop on Discourse in Machine Translation (DiscoMT2015). The release also contains the submissions to the pronoun-focused machine translation along with the manual annotations used for the official evaluation as well as gold-standard annotations of pronoun coreference for the shared task test set.
DOESTE v0.5 is a set of developmental corpora of texts written by Brazilian and Portuguese school-age children and adolescents. It is a work in progress.
The texts written by monolingual children and adolescents in European Portuguese were collected between September 2011 and January 2012, from different public schools in Lisbon (Portugal). It is composed of 244 narrative (n=122) and argumentative (n=122) texts. The subjects (51% female and 49% male) are students enroled in the 5th grade (n=52; mean age=10.19), in the 7th grade (n=92; mean age=12.33) and in the 10th grade (n=100; mean age=15.16) from the Portuguese basic schooling. The subcorpus of Portuguese texts is fully tokenized and morphologically annotated, in addition to presenting the sentence occurrences.
The texts written by monolingual children and adolescents in Brazilian Portuguese have been collected since 2017, from different public schools in three cities in Rio Grande do Norte (Brazil). It is currently composed of narrative (n=225) and argumentative (n=225) texts. The subjects (53% female and 47% male) are students enroled in the 5th grade (n=68; mean age=11.13), in the 9th grade (n=82; mean age=15.32) and in the 12th grade (n=224; mean age=17.96) from the Brazilian basic schooling. The subcorpora of Brazilian texts is still in the compilation, but a large part is already searchable, being tokenized and morphologically annotated. The Brazilian subcorpus also presents itself with the original transcripts, along original images.
Portuguese and Brazilian texts were collected from similar tasks:
Narrative-based task: Tell a remarkable story (real or imagined) that you and your best friend lived during the last school vacation.
Argumentative based-task: Do you think social networks (Facebook, Twitter, Google+, Windows Live Space, etc.) are important today? Write a text to be published on your school's blog where you express your opinion on social networks. In this text, you must say whether you are for or against the existence of social networks. Don't forget to justify your opinion!
The next version of DOESTE intends to present semantic annotations and clause and t-unit segmentation.
DOESTE v0.5 is developed and maintained by the Educational Linguistics Research Group (LEd), based at the Federal Rural University of the Semiarid Region (UFERSA).
DOESTE v0.5 by Mário Martins et al. is licensed under CC BY-NC-ND 4.0.
Modifications to DSpace made by Petr Pajas in order to support pidconsortium.eu PID handle system instead of the default handle.com system used by DSpace.
DZ Interset is a means of converting among various tag sets in natural language processing. The core idea is similar to interlingua-based machine translation. DZ Interset defines a set of features that are encoded by the various tag sets. The set of features should be as universal as possible. It does not need to encode everything that is encoded by any tag set but it should encode all information that people may want to access and/or port from one tag set to another.
New tag sets are attached by writing a driver for them. Once the driver is ready, you can easily convert tags between the new set and any other set for which you also have a driver. This reusability is an obvious advantage over writing a targeted conversion procedure each time you need to convert between a particular pair of tag sets. and grant MSM 0021620838 of the Ministry of Education of the Czech Republic
This software package includes three tools: web frontend for machine translation featuring phonetic transcription of Ukrainian suitable for Czech speakers, API server and a tool for translation of documents with markup (html, docx, odt, pptx, odp,...). These tools are used in the Charles Translator service (https://translator.cuni.cz).
This software was developed within the EdUKate project, which aims to help mitigate language barriers between non-Czech-speaking children in the Czech Republic and the education in the Czech school system. The project focuses on the development and dissemination of multilingual digital learning materials for students in primary and secondary schools.