The database lists translations of Irish literature into Czech and Slovak from the times of the Czech and Slovak national revivals to the present day, as well as Czech and Slovak reflections on Ireland and Irish culture from the earliest records up until the present (Slovak reflections being covered up to the 1990s). A detailed outline of the coverage of the database and sources of the data is available at https://irbiblio.ff.cuni.cz/about. Originally developed in the early 2000s by Daniel Samek, the database has been maintained and continuously updated by the Centre for Irish Studies of the Faculty of Arts, Charles University. The irbiblio_2026-06-09.csv contains all the data in a flat (one table) CSV format, while irbiblio_2026-06-09.sql is the dump of the same data from a relational database.

AI Brown is a corpus of English texts generated with large language models (LLMs). Its main purpose is to create a resource for comparing human-written texts with LLM-generated text linguistically. The corpus is multi-genre and rich in terms of topics, authors, and text types, and comparable with existing human-created corpora. The corpus replicates the reference human BE21 corpus by Paul Baker, a modern version of the original Brown Corpus. The new corpus was generated using 25 models from OpenAI, Anthropic, Google, Meta, and DeepSeek, ranging from GPT-3 (davinci-002) to recent frontier models such as GPT-5.4, Claude 4.7, and Gemini 3.1, and is tagged according to the Universal Dependencies standard (i.e., the texts are tokenized, lemmatized, and morphologically and syntactically annotated). The subcorpus size varies according to the model used (on average 959k tokens per subcorpus, 47.0M tokens altogether across 49 subcorpora). The raw data and plain texts are freely available for download under the CC BY 4.0 license, the UD annotated data are under CC BY-NC-SA 4.0 licence. The corpus is also accessible through the KonText search interface of the Czech National Corpus (https://www.korpus.cz/kontext/query?corpname=ai_brown_v2).

AI Koditex is a corpus of Czech texts generated with large language models (LLMs). Its main purpose is to create a resource for comparing human-written texts with LLM-generated text linguistically. The corpus is multi-genre and rich in terms of topics, authors, and text types, and comparable with existing human-created corpora. The corpus replicates the reference human Koditex corpus that follows the Brown Corpus tradition. The new corpus was generated using 24 models from OpenAI, Anthropic, Google, Meta, and DeepSeek, ranging from GPT-3 (davinci-002) to recent frontier models such as GPT-5.4, Claude 4.7, and Gemini 3.1, and is tagged according to the Universal Dependencies standard (i.e., the texts are tokenized, lemmatized, and morphologically and syntactically annotated). The subcorpus size varies according to the model used (on average 813k tokens per subcorpus, 36.6M tokens altogether across 45 subcorpora). The raw data and plain texts are freely available for download under the CC BY 4.0 license, the UD annotated data are under CC BY-NC-SA 4.0 licence. The corpus is also accessible through the KonText search interface of the Czech National Corpus (https://www.korpus.cz/kontext/query?corpname=ai_koditex_v2).