aimgo/Simulacrum

Si machina nullo moderatore aberrasset...

About

This dataset features human authored text, mined from Acervus, annotated by multiple LLMs with 5 different span relations and inferred genre. The organic examples are paired with machine authored modifications.

It also contains a number of hallucinated or adversarial Latin-like examples which pass lexical filters but are semantically or grammatically incoherent. Additionally, there are some 10,000 samples created by a variety of Lorem Ipsum generators.

These include highly adversarial samples which contain imagined Latin forms, no discernible syntax, or are completely incoherent.

Atrius Tubulus consul centum senatus consultum triumphi non sregio pugnāvis
 ob sidera accipiet aga specta dimidia parte multa vis sed

Pseudo Latin can be observed across multiple different registers, further complicating detection:

conglutinatus est in hodie restandum quod vobis Et terra venter noster Clamabat que
ad dixerunt Monstra calumniatus nos Dominus

Relations

• NLI Logical Entailment (premise-hypothesis)
• Question Answering (question-answer)
• Quote Attribution (quote-attribution)
• Dialogue e.g. chat (utterance-reply)
• Prompt-Response, e.g. temporal succession, narrative sequence, or thematic association (prompt-response)

Categorical

• Text Genre (ecclesiastical, historiography, law, treatise, poetry, rhetoric, general, satire)
• Adversarial Highly-Latin-Like Text (Pseudo-Latin, Lorem Ipsum, & Hallucinated Latin that evaded aggressive lexical filtering)

Machine Modification

• Human Original vs. Machine Authored Back Translation (human-machine)
• Original vs. Machine Authored Translation (lat-eng)

Counts

Total rows: 101594

models:

Model	Count
claude-opus-5-5	52486
gpt-6.1-sol	37112
LoremGenerators	11996

categories:

Category	Count
treatise	24888
pseudo	19732
ecclesiastical	18379
historiography	11869
poetry	11005
rhetoric	5753
general	5232
law	4259
satire	477

relations:

Relation	Count
machine-authorship	31800
machine-translation	26515
quote-attribution	7670
premise-hypothesis	7179
prompt-response	6106
question-answer	1643
dialogue	974

Citation

If you use this, please cite:

@misc{mccarthy2026Simulacrum,
  author       = {McCarthy, Aidan},
  title        = {{Simulacrum}: Machine Authored and Annotated Latin},
  year         = {2026},
  howpublished = {\url{https://huggingface.co/datasets/aimgo/Simulacrum}},
  note         = {Dataset}
}