Triple
T29534276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doctor Poison (DCEU) |
E749291
|
entity |
| Predicate | costumeDesignerForDepiction |
P36430
|
FINISHED |
| Object | Lindy Hemming |
—
|
NE NERFINISHED |
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: Lindy Hemming | Statement: [Doctor Poison (DCEU), costumeDesignerForDepiction, Lindy Hemming]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: costumeDesignerForDepiction Context triple: [Doctor Poison (DCEU), costumeDesignerForDepiction, Lindy Hemming]
-
A.
costumeDesignerOfWork
Indicates that an entity serves as the costume designer responsible for the costumes in a particular creative work.
-
B.
costumeDesignEmphasisOn
Indicates that a costume design places particular focus or priority on a specified element, style, feature, or thematic aspect.
-
C.
designedCostumesFor
chosen
Indicates that one entity created or planned the costumes used by another entity, typically for a performance, production, or event.
-
D.
costumeDesignStyle
Indicates the stylistic approach or aesthetic characteristics used in designing a costume for a character or production.
-
E.
depicts costume
Indicates that one entity visually represents or portrays the clothing or outfit associated with another entity.
- 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_69f0bd47abb081909bd6e6a33d770fd8 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f66cc56c5081908ff1eb9d5a848635 |
completed | May 2, 2026, 9:29 p.m. |
| PD | Predicate disambiguation | batch_69f6633ac8a88190ab0cda62bbfcf9b0 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 4:56 p.m.