Triple
T35709407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Un bon bock |
E1031810
|
entity |
| Predicate | firstScreeningCountry |
—
|
GENERATED |
| Object | France |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstScreeningCountry Context triple: [Un bon bock, firstScreeningCountry, France]
-
A.
firstForCountry
Indicates that the subject is the first instance or occurrence of its type to happen or exist within the specified country.
-
B.
positionInceptionCountry
Indicates the country in which a given position, role, or office was originally established or came into existence.
-
C.
countryOfPremiere
chosen
Indicates the country in which a work (such as a film, show, or performance) was first publicly premiered.
-
D.
primaryLocationCountry
Indicates the country that serves as the main or primary location associated with the subject.
-
E.
wasFirstPerformedInCountry
Indicates that an action, event, or work was first performed within the borders of a specified country.
- F. None of above.
Provenance (1 batch)
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_69f76e0df1d08190965b1c6dff94c391 |
completed | May 3, 2026, 3:47 p.m. |
Created at: May 3, 2026, 4:05 p.m.