Triple
T27521873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Ain’t Worried |
E694728
|
entity |
| Predicate | featuresInSceneType |
P61635
|
FINISHED |
| Object | beach football scene in Top Gun: Maverick |
—
|
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: beach football scene in Top Gun: Maverick | Statement: [I Ain’t Worried, featuresInSceneType, beach football scene in Top Gun: Maverick]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresInSceneType Context triple: [I Ain’t Worried, featuresInSceneType, beach football scene in Top Gun: Maverick]
-
A.
sceneFeature
chosen
Indicates a characteristic, element, or attribute that is present within or helps define a particular scene.
-
B.
featureTypeCatalog
Indicates that an entity is associated with, or defined by, a catalog that specifies the types of features it can include or reference.
-
C.
featuresSceneFrom
Indicates that one entity (such as a work or media item) includes or presents a particular scene taken from another entity.
-
D.
featuresIn
Indicates that an entity appears or plays a role within another entity, such as a person or element being included in a work, event, or context.
-
E.
filmSceneType
Indicates the type or category of a scene within a film, such as its narrative function, style, or setting.
- 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_69ef538550208190aa9de8e2cb260d93 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69fd553d7cb881908d243e7a9f30ac85 |
completed | May 8, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69fd514dcb1c81908333c70d7edd79c9 |
completed | May 8, 2026, 2:58 a.m. |
Created at: April 27, 2026, 1:21 p.m.