Triple
T3494059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camille (1921 film) – costume and set design |
E73804
|
entity |
| Predicate | typeOfCostumes |
P5541
|
FINISHED |
| Object | evening gowns and formal wear |
—
|
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: evening gowns and formal wear | Statement: [Camille (1921 film) – costume and set design, typeOfCostumes, evening gowns and formal wear]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfCostumes Context triple: [Camille (1921 film) – costume and set design, typeOfCostumes, evening gowns and formal wear]
-
A.
costumeType
chosen
Indicates the specific kind or category of costume associated with an entity.
-
B.
numberOfCostumes
Indicates the total count of costumes associated with or used by a given entity.
-
C.
costumeElement
Indicates that one item functions as a component or part of another item's costume.
-
D.
designedCostumesFor
Indicates that one entity created or planned the costumes used by another entity, typically for a performance, production, or event.
-
E.
costumesDisplayedAt
Indicates that certain costumes are being shown or exhibited at a particular location or event.
- 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_69ad85cdb6e48190a335d412b9194ed8 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbbaebed881909d9cbc9c4c1f138f |
completed | March 8, 2026, 6:10 p.m. |
| PD | Predicate disambiguation | batch_69adae0b34908190b2bb5766a2231f7a |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:18 p.m.