Triple
T12030721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Verona Beach |
E286396
|
entity |
| Predicate | notableSceneLocationFor |
P15715
|
FINISHED |
| Object | gas station shootout |
—
|
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: gas station shootout | Statement: [Verona Beach, notableSceneLocationFor, gas station shootout]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableSceneLocationFor Context triple: [Verona Beach, notableSceneLocationFor, gas station shootout]
-
A.
notableScene
Indicates that a particular scene is especially significant, memorable, or noteworthy within a work or context.
-
B.
notableLocation
Indicates that a location is especially significant, prominent, or noteworthy in relation to the subject.
-
C.
notableShowLocation
Indicates that a show or performance is notably associated with, took place at, or is best known for occurring in a particular location.
-
D.
notableFilmingLocation
Indicates that a place served as a significant or well-known location where a film or television production was shot.
-
E.
notableLocationFeatured
chosen
Indicates that a particular location is prominently highlighted or showcased in relation to the subject.
- 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_69d6ab4669e48190b59246358b0383ab |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902b6ebbc8190b13c44a61c6f81b9 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:47 p.m.