Triple
T36303570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Antonia Dreykov |
E893885
|
entity |
| Predicate | costumeIdentity |
P63559
|
FINISHED |
| Object | Taskmaster armor |
—
|
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: Taskmaster armor | Statement: [Antonia Dreykov, costumeIdentity, Taskmaster armor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: costumeIdentity Context triple: [Antonia Dreykov, costumeIdentity, Taskmaster armor]
-
A.
isCostumedCharacterFor
Indicates that one entity serves as a costumed character representation or mascot for another entity, typically for promotional or entertainment purposes.
-
B.
costume
chosen
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.
costumeContext
Indicates the situational or narrative context in which a costume is used, such as the event, setting, or role it is associated with.
-
E.
isCostumed
Indicates that an entity is wearing or otherwise adorned with 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_69f76e4c1b248190b10667d0213537fe |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7ba6d06f48190a71b5a2f19e2232f |
completed | May 3, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a4aad48190a62e41c5e39339d9 |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:09 p.m.