Triple

T7916206
Position Surface form Disambiguated ID Type / Status
Subject Claude-Louis Navier E183834 entity
Predicate familyName P18 FINISHED
Object Navier E173917 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: Navier | Statement: [Claude-Louis Navier, familyName, Navier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Navier
Context triple: [Claude-Louis Navier, familyName, Navier]
  • A. Navier chosen
    Navier is a French surname most notably associated with Claude-Louis Navier, a pioneering engineer and physicist in fluid mechanics and elasticity theory.
  • B. Drouet
    Drouet is a French surname most notably associated with Jean-Baptiste Drouet, the postmaster who helped identify and arrest King Louis XVI during his attempted flight in 1791.
  • C. Serrault
    Serrault is a French surname most famously borne by Michel Serrault, the acclaimed actor known for his work in film, theater, and television.
  • D. Bouchet
    Bouchet is a surname most notably associated with Edward Alexander Bouchet, one of the first African Americans to earn a Ph.D. in the United States.
  • E. Lagrenée
    Lagrenée is a French surname most notably associated with the 18th-century painter Louis Lagrenée.
  • 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_69ca828efbe48190bd48482650182e79 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3a76ae688190b068e4c92603a16d completed March 31, 2026, 3:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5be54fdc81909a988114a6f30a13 completed March 31, 2026, 5:30 a.m.
Created at: March 30, 2026, 5:05 p.m.