Triple
T30156745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Carpet Massacre |
E766542
|
entity |
| Predicate | featuresContemporarySound |
P201167
|
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: [Red Carpet Massacre, featuresContemporarySound, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresContemporarySound Context triple: [Red Carpet Massacre, featuresContemporarySound, true]
-
A.
hasMoreContemporarySound
Indicates that one entity’s sound or style is perceived as more modern or up-to-date compared to another.
-
B.
exploresSound
Indicates that an entity actively investigates, experiments with, or examines sound or audio-related phenomena.
-
C.
showcasesSoundOf
Indicates that one entity presents or highlights the characteristic sound produced by another entity.
-
D.
featuresRichHarmonies
Indicates that the subject contains or employs complex, layered, and sonically dense harmonic structures.
-
E.
hasAcousticsSuitableFor
Indicates that something possesses acoustic properties that are appropriate or well-suited for a particular use, activity, or environment.
- 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_69f22479cd088190ab4c6f3fce39d1c5 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69ffcf46fd688190907fd1ceb499a8d1 |
completed | May 10, 2026, 12:20 a.m. |
| PD | Predicate disambiguation | batch_69ffccde2a8c81908e055e74077dbd19 |
completed | May 10, 2026, 12:10 a.m. |
| PDg | Predicate description generation | batch_69ffcf4631cc8190aefa4b8f0b940b89 |
completed | May 10, 2026, 12:20 a.m. |
Created at: April 29, 2026, 7:21 p.m.