Triple
T7678120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Claude-Louis Navier |
E173917
|
entity |
| Predicate | hasSurname |
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, hasSurname, Navier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Navier Context triple: [Claude-Louis Navier, hasSurname, 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_69c6995703e0819081de77361b602e78 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c701fd18d88190888144a7d0f228d9 |
completed | March 27, 2026, 10:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8a240057081908826a5371ef5215b |
completed | March 29, 2026, 3:53 a.m. |
Created at: March 27, 2026, 4:01 p.m.