Triple
T16953522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rising Star |
E411239
|
entity |
| Predicate | subgenreOfScene |
P15287
|
FINISHED |
| Object | trance 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: trance scene | Statement: [Rising Star, subgenreOfScene, trance scene]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subgenreOfScene Context triple: [Rising Star, subgenreOfScene, trance scene]
-
A.
subgenre
chosen
Indicates that one genre is a more specific, subordinate category within a broader parent genre.
-
B.
filmSceneType
Indicates the type or category of a scene within a film, such as its narrative function, style, or setting.
-
C.
secondaryGenre
Indicates that an entity (such as a work or item) has an additional, non-primary genre classification associated with it.
-
D.
visualGenre
Indicates the visual or stylistic category to which something belongs, such as its artistic or cinematic genre.
-
E.
associatedWithGenreScene
Indicates that an entity is connected or related to a particular genre scene, such as a specific stylistic or cultural subcommunity within a broader genre.
- 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_69d886c9c9d481909afe222093641cae |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d01a4ae8819085a6ce01fbc71b0f |
completed | April 18, 2026, 6:40 p.m. |
| PD | Predicate disambiguation | batch_69e32b9aa8748190b248890aca86753d |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:31 a.m.