Triple
T12930001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Étienne Marcel |
E309349
|
entity |
| Predicate | isNamedForRoleOfEponym |
P53948
|
FINISHED |
| Object | provost of the merchants of Paris |
—
|
LITERAL 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: provost of the merchants of Paris | Statement: [Étienne Marcel, isNamedForRoleOfEponym, provost of the merchants of Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isNamedForRoleOfEponym Context triple: [Étienne Marcel, isNamedForRoleOfEponym, provost of the merchants of Paris]
-
A.
isNamedForEponymRole
chosen
Indicates that one entity bears a name derived from another entity that serves as its eponym or namesake.
-
B.
isNamedForPersonFrom
Indicates that an entity is named after a person who originates from a specified place or region.
-
C.
isNamedFor
Indicates that one entity bears its name in honor of, or derived from, another entity.
-
D.
eponymFor
Indicates that one entity gives its name to another entity, which is then named after it.
-
E.
hasEponymConnectionTo
Indicates that one entity is named after, derived from, or otherwise linguistically or honorifically connected to another entity as its eponym.
- F. None of above.
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_69d7bdfa933c8190b5a27aa4a08a19b7 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97245b6408190816d9b7e314eb51a |
completed | April 10, 2026, 9:57 p.m. |
| PD | Predicate disambiguation | batch_69d96fab4d0881909a7a4d66bab9aa85 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:42 p.m.