Triple
T9539433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Napoleon I |
E230108
|
entity |
| Predicate | createdTitle |
P38
|
FINISHED |
| Object | duc de Plaisance |
E230108
|
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: duc de Plaisance | Statement: [Napoleon I, createdTitle, duc de Plaisance]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: duc de Plaisance Context triple: [Napoleon I, createdTitle, duc de Plaisance]
-
A.
duc de Plaisance
chosen
The duc de Plaisance was a French ducal title created by Napoleon for statesman Charles-François Lebrun, one of the First French Empire’s leading political figures.
-
B.
Caussade
Caussade is a commune in southern France known for its hat-making heritage and location within the Tarn-et-Garonne department in the Occitanie region.
-
C.
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.
-
D.
Lagrenée
Lagrenée is a French surname most notably associated with the 18th-century painter Louis Lagrenée.
-
E.
Barbaroux
Barbaroux is a French surname most notably associated with Charles Barbaroux, a prominent figure of the French Revolution.
- 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_69ca847b1b3081908f72bc932c17cc41 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98e4df6c8190a4d1160c42daa45f |
completed | April 1, 2026, 10:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d15278efd4819091e707aabd9a59d7 |
completed | April 4, 2026, 6:03 p.m. |
Created at: March 30, 2026, 8:01 p.m.