Triple
T16827851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Jackson's Thriller (music video) |
E409065
|
entity |
| Predicate | featuresIconicCostume |
P58290
|
FINISHED |
| Object | red leather jacket worn by Michael Jackson |
—
|
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: red leather jacket worn by Michael Jackson | Statement: [Michael Jackson's Thriller (music video), featuresIconicCostume, red leather jacket worn by Michael Jackson]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresIconicCostume Context triple: [Michael Jackson's Thriller (music video), featuresIconicCostume, red leather jacket worn by Michael Jackson]
-
A.
costumeFeatures
chosen
Indicates that a costume possesses or includes specific features, attributes, or decorative elements.
-
B.
costume
Indicates that one entity is wearing, dressed in, or outfitted with the other entity as a costume.
-
C.
costumeType
Indicates the specific kind or category of costume associated with an entity.
-
D.
costumeElement
Indicates that one item functions as a component or part of another item's costume.
-
E.
colorAssociatedWithCostume
Indicates that a particular color is thematically or typically linked to a specific costume.
- 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_69d88394566c8190b3dcbdc72935f7fa |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b3151350819097b1c375e6df8986 |
completed | April 18, 2026, 4:36 p.m. |
| PD | Predicate disambiguation | batch_69e32b814b188190aee525f8779203cd |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:23 a.m.