Triple

T10258802
Position Surface form Disambiguated ID Type / Status
Subject Madrid Codices E240541 entity
Predicate author P4 FINISHED
Object Leonardo da Vinci E22299 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Leonardo da Vinci | Statement: [Madrid Codices, author, Leonardo da Vinci]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leonardo da Vinci
Context triple: [Madrid Codices, author, Leonardo da Vinci]
  • A. Leonardo da Vinci chosen
    Leonardo da Vinci was a Renaissance polymath renowned as a master painter, inventor, scientist, and engineer whose works and ideas profoundly influenced art and science.
  • B. Leonardo
    Leonardo is the katana-wielding, blue-masked leader of the Teenage Mutant Ninja Turtles in the popular comic, TV, and film franchise.
  • C. Leonardo
    Leonardo is the first name of Leonardo DiCaprio, the acclaimed American actor and environmental activist known for films such as Titanic and Inception.
  • D. Michelangelo
    Michelangelo was a Renaissance master renowned as a sculptor, painter, and architect, celebrated for works such as the Sistine Chapel ceiling and the design of major religious structures in Rome.
  • E. Michelangelo
    Michelangelo is the fun-loving, pizza-obsessed, nunchuck-wielding Ninja Turtle known for his goofy humor and carefree attitude.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d381a7e198819090280d5ab885d59e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d24e94e08190ad2b9733bf621fe4 completed April 7, 2026, 9:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f7e9a9d48190865f047750d7bc6c completed April 9, 2026, 12:50 a.m.
Created at: April 6, 2026, 11:31 a.m.