Triple
T21741317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joseph Fouché |
E536664
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Fouché |
—
|
NE NERFINISHED |
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: Fouché | Statement: [Joseph Fouché, familyName, Fouché]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fouché Context triple: [Joseph Fouché, familyName, Fouché]
-
A.
Joseph Fouché
chosen
Joseph Fouché was a powerful and controversial French statesman and police minister who played a key role in the politics and security apparatus of Revolutionary and Napoleonic France.
-
B.
Jean-Jacques Rifaud
Jean-Jacques Rifaud was a 19th-century French explorer and antiquarian known for his archaeological work and artifact collecting in Egypt.
-
C.
Mirabeau
Mirabeau is the given name of Mirabeau B. Lamar, the second president of the Republic of Texas and a prominent 19th-century American political figure.
-
D.
Mirabeau
Mirabeau is a famous tight right-hand corner on the Monaco Grand Prix street circuit, known for its downhill approach and importance for overtaking and race strategy.
-
E.
Mirabeau
Mirabeau is a picturesque commune in southeastern France, known for its Provençal landscapes and historic village setting.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c46df5448190b4322127ffc4c690 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01a7250d48190aa63f89db017ef70 |
completed | April 28, 2026, 2:24 a.m. |
Created at: April 16, 2026, 6:49 p.m.