Triple
T9367246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Girl Hunt Ballet |
E225431
|
entity |
| Predicate | costumeDesignFeature |
P58290
|
FINISHED |
| Object | trench coat and fedora for detective |
—
|
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: trench coat and fedora for detective | Statement: [Girl Hunt Ballet, costumeDesignFeature, trench coat and fedora for detective]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: costumeDesignFeature Context triple: [Girl Hunt Ballet, costumeDesignFeature, trench coat and fedora for detective]
-
A.
costumeFeatures
chosen
Indicates that a costume possesses or includes specific features, attributes, or decorative elements.
-
B.
costumeDesignNotability
Indicates that an entity is notable or recognized specifically for its work or achievements in costume design.
-
C.
costumeDesignStyle
Indicates the stylistic approach or aesthetic characteristics used in designing a costume for a character or production.
-
D.
costumeElement
Indicates that one item functions as a component or part of another item's costume.
-
E.
costume
Indicates that one entity is wearing, dressed in, or outfitted with the other entity as a 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_69ca842cbddc819099d71ecec48cf9e5 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd5042c89c8190994b12cf7600c366 |
completed | April 1, 2026, 5:05 p.m. |
| PD | Predicate disambiguation | batch_69cc7a6abb8c81908c7a2f4ee92cc949 |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:43 p.m.