Triple
T17184464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Precious Thing |
E417067
|
entity |
| Predicate | isAssociatedWithLabelScene |
P126652
|
FINISHED |
| Object | Touch and Go Records roster |
—
|
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: Touch and Go Records roster | Statement: [Precious Thing, isAssociatedWithLabelScene, Touch and Go Records roster]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isAssociatedWithLabelScene Context triple: [Precious Thing, isAssociatedWithLabelScene, Touch and Go Records roster]
-
A.
hasInfluenceFromScene
Indicates that something is affected, shaped, or guided by the characteristics or context of a particular scene.
-
B.
notableLabelScene
Indicates that a particular scene is notably associated with, or prominently labeled by, a specific tag, title, or descriptor.
-
C.
containsScene
Indicates that one entity (typically a media item or narrative work) includes or features a particular scene as part of its content.
-
D.
sceneLabel
Indicates the categorical label or type assigned to an entire scene based on its overall content or context.
-
E.
judgmentSceneAssociatedWith
Indicates that a particular judgment or evaluation event is contextually linked or relevant to a specific scene or situational setting.
- 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_69d886d5f34c8190b24564dfaa63f3fb |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42d9556c881908ccaee4ef77dbe1f |
completed | April 19, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69e383141ae0819096acd71683637cbc |
completed | April 18, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69e39c2fedb881908bfed2c3e5f2616a |
completed | April 18, 2026, 2:58 p.m. |
Created at: April 10, 2026, 5:37 a.m.