Triple
T36140270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Gamblers |
E1045277
|
entity |
| Predicate | regionScene |
P84945
|
FINISHED |
| Object | Southern California surf scene |
—
|
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: Southern California surf scene | Statement: [The Gamblers, regionScene, Southern California surf scene]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionScene Context triple: [The Gamblers, regionScene, Southern California surf scene]
-
A.
partOfScene
Indicates that one entity functions as a component or element within a larger scene or setting involving another entity.
-
B.
centralScene
Indicates that one scene functions as the main or focal scene within a larger narrative, sequence, or composition.
-
C.
hasRegionalScene
chosen
Indicates that something possesses or is associated with a specific regional scene, such as a localized cultural, artistic, or social milieu.
-
D.
sceneFeature
Indicates a characteristic, element, or attribute that is present within or helps define a particular scene.
-
E.
featuresSceneFrom
Indicates that one entity (such as a work or media item) includes or presents a particular scene taken from another entity.
- 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_69f76e36a4508190b5bfc8f594272a4c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a000efe971081909de03f875a7ad6cc |
completed | May 10, 2026, 4:52 a.m. |
| PD | Predicate disambiguation | batch_6a000c4ffe788190a5757af60aadd9f3 |
completed | May 10, 2026, 4:40 a.m. |
Created at: May 3, 2026, 4:08 p.m.