Triple
T5537313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | When a Man Loves |
E145193
|
entity |
| Predicate | hasCostumeDesign |
P1529
|
FINISHED |
| Object | period costumes |
—
|
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: period costumes | Statement: [When a Man Loves, hasCostumeDesign, period costumes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCostumeDesign Context triple: [When a Man Loves, hasCostumeDesign, period costumes]
-
A.
designedCostumesFor
Indicates that one entity created or planned the costumes used by another entity, typically for a performance, production, or event.
-
B.
costumeDesignStyle
Indicates the stylistic approach or aesthetic characteristics used in designing a costume for a character or production.
-
C.
hasDesign
chosen
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
D.
costumeDesignNotability
Indicates that an entity is notable or recognized specifically for its work or achievements in costume design.
-
E.
haveDistinctCostume
Indicates that the entities each possess a costume that is different from the others’ costumes.
- 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_69c008fa64888190adae56c8f9ea4031 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01fb19cb8819088b21e8ebef63d8b |
completed | March 22, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69c01b0c50e48190a1b03ecd20ca440b |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:34 p.m.