Triple
T34005638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Virtual Diva (Remix) |
E871952
|
entity |
| Predicate | hasDancefloorFocus |
P178145
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Virtual Diva (Remix), hasDancefloorFocus, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDancefloorFocus Context triple: [Virtual Diva (Remix), hasDancefloorFocus, true]
-
A.
hasDanceFloor
Indicates that a place or venue includes a designated area intended for dancing.
-
B.
hasDanceFloorEnergy
chosen
Indicates that an entity exhibits a lively, engaging, and energetic presence suitable for a dance floor atmosphere.
-
C.
hasDancefloorReputation
Indicates that an entity is known or reputed for its behavior, status, or recognition on the dancefloor.
-
D.
hasDanceFocusedProduction
Indicates that a production is primarily centered on or dedicated to dance as its main artistic focus.
-
E.
hasDiningFocus
Indicates that an entity is primarily oriented toward or specialized in dining-related activities, services, or experiences.
- 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_69f349a08848819084b348d64c1879c3 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f70fb4f18c819099ef6d9177b7d205 |
completed | May 3, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69f70f3a54d481909ba6bdda3647b761 |
completed | May 3, 2026, 9:02 a.m. |
Created at: May 1, 2026, 1:50 a.m.