Triple
T33344525
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Republic of Zubrowka |
E853758
|
entity |
| Predicate | filmingLocationStandIn |
P176520
|
FINISHED |
| Object | Germany |
—
|
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: Germany | Statement: [Republic of Zubrowka, filmingLocationStandIn, Germany]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmingLocationStandIn Context triple: [Republic of Zubrowka, filmingLocationStandIn, Germany]
-
A.
filmingLocationContext
Indicates the contextual relationship specifying where the filming of an event, scene, or production took place.
-
B.
filmingStudio
Indicates that a studio is responsible for producing or filming a particular audiovisual work.
-
C.
formerFilmingLocation
Indicates that a place was once used as a filming location for a work but is no longer used for that purpose.
-
D.
filmingLocationForAdaptation
Indicates the place where an adaptation (such as a film or TV version of a work) was shot or recorded.
-
E.
filmingLocationPattern
Indicates the typical or recurring geographic pattern of locations where filming for a production takes place.
- F. None of above. chosen
Provenance (4 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_69f3496a1a588190bad9cbe9221144e0 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6e3156ea48190b604e414665ef351 |
completed | May 3, 2026, 5:54 a.m. |
| PD | Predicate disambiguation | batch_69f6de0b9ba48190887c9eb5d06a2e94 |
completed | May 3, 2026, 5:32 a.m. |
| PDg | Predicate description generation | batch_69f6e312d7fc819094dec41810f2585d |
completed | May 3, 2026, 5:54 a.m. |
Created at: May 1, 2026, 1:34 a.m.