Triple
T27951913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sweet Sensation |
E703447
|
entity |
| Predicate | sceneAssociation |
P163985
|
FINISHED |
| Object | warehouse parties |
—
|
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: warehouse parties | Statement: [Sweet Sensation, sceneAssociation, warehouse parties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sceneAssociation Context triple: [Sweet Sensation, sceneAssociation, warehouse parties]
-
A.
notableSceneAssociation
Indicates an association between an entity and a notable or memorable scene in which it prominently appears or plays a significant role.
-
B.
sceneRelationship
Indicates a contextual or spatial relationship that links entities based on how they co-occur or interact within the same scene.
-
C.
sceneFeature
Indicates a characteristic, element, or attribute that is present within or helps define a particular scene.
-
D.
isAssociatedWithLabelScene
Indicates that an entity is connected to or involved with a particular labeled scene or scene annotation.
-
E.
sceneLabel
Indicates the categorical label or type assigned to an entire scene based on its overall content or context.
- 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_69ef840c8b2c8190946ae9522774ba51 |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f6416fbf4081909b0913c337927fc4 |
completed | May 2, 2026, 6:24 p.m. |
| PD | Predicate disambiguation | batch_69f63c6895f0819088655277e45859a8 |
completed | May 2, 2026, 6:03 p.m. |
| PDg | Predicate description generation | batch_69f63fd4f7448190930c723ba7cfce62 |
completed | May 2, 2026, 6:17 p.m. |
Created at: April 27, 2026, 7:25 p.m.