Triple
T28664688
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zihuatanejo (in film ending) |
E725555
|
entity |
| Predicate | filmingLocationForBeachScene |
P165191
|
FINISHED |
| Object | Saint Croix, U.S. Virgin Islands |
—
|
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: Saint Croix, U.S. Virgin Islands | Statement: [Zihuatanejo (in film ending), filmingLocationForBeachScene, Saint Croix, U.S. Virgin Islands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmingLocationForBeachScene Context triple: [Zihuatanejo (in film ending), filmingLocationForBeachScene, Saint Croix, U.S. Virgin Islands]
-
A.
filmingLocationContext
Indicates the contextual relationship specifying where the filming of an event, scene, or production took place.
-
B.
filmingLocationPattern
Indicates the typical or recurring geographic pattern of locations where filming for a production takes place.
-
C.
placeOfShooting
Indicates the location where a shooting event took place.
-
D.
filmingLocationCity
Indicates the city where the filming or recording of a work took place.
-
E.
filmingLocationForAdaptation
Indicates the place where an adaptation (such as a film or TV version of a work) was shot or recorded.
- 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_69f01d85be388190b669a0e401e2f2c4 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f65705a3048190a3728b695ba2ae65 |
completed | May 2, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69f651ac855481908e30c3b345d31356 |
completed | May 2, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69f6562ef4e4819082ce6abd41b74dc5 |
completed | May 2, 2026, 7:53 p.m. |
Created at: April 28, 2026, 5 a.m.