AI Brown v1

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 comparabile with existing human-created corpora. The corpus replicates reference human corpus: BE21 by Paul Baker, which is a modern version of the original Brown Corpus. The new corpus was generated using models from OpenAI, Anthropic, Alphabet, Meta, and DeepSeek, ranging from GPT-3 (davinci-002) to GPT-4.5, and are 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 (864k tokens per model on average, 27.7M tokens altogether). 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_v1).