Triple
T164543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | G-Wiz |
E2983
|
entity |
| Predicate | costumeType |
P5541
|
FINISHED |
| Object | costumed character |
—
|
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: costumed character | Statement: [G-Wiz, costumeType, costumed character]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: costumeType Context triple: [G-Wiz, costumeType, costumed character]
-
A.
wears
Indicates that one entity is dressed in, or has on its body, a particular item such as clothing or accessories.
-
B.
coneType
Indicates the specific category or style of cone associated with an entity (e.g., type, shape, or design of the cone).
-
C.
hasDressCode
Indicates that a specified entity enforces or is associated with a particular set of rules governing appropriate clothing or attire.
-
D.
ceremonyType
Indicates the specific kind or category of ceremony associated with an event or relationship.
-
E.
displayOccasion
Indicates the event, context, or situation during which something is presented, shown, or made visible.
- F. None of above. chosen
Provenance (4 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_69a2524ce1e48190ab066bf72859f474 |
completed | Feb. 28, 2026, 2:26 a.m. |
| NER | Named-entity recognition | batch_69a258827da481909b20ea5e9d21676f |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a2566392208190a538ea9aa1fac53e |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a257101060819094db0f3a3a72f312 |
completed | Feb. 28, 2026, 2:46 a.m. |
Created at: Feb. 28, 2026, 2:34 a.m.