Triple
T38593392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caduceus Blaster |
E932504
|
entity |
| Predicate | hasIconInHUD |
P191268
|
FINISHED |
| Object | True |
—
|
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: True | Statement: [Caduceus Blaster, hasIconInHUD, True]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIconInHUD Context triple: [Caduceus Blaster, hasIconInHUD, True]
-
A.
hasIcons
Indicates that one entity possesses, includes, or is associated with one or more icons in relation to another entity or context.
-
B.
hasStationIcon
Indicates that an entity is associated with a specific icon used to visually represent a station.
-
C.
hasIconicArea
Indicates that an entity possesses a distinct, widely recognized area or region that is emblematic or characteristic of it.
-
D.
hasIconographicFigure
Indicates that one entity includes, depicts, or is associated with a particular iconographic figure in its visual or symbolic representation.
-
E.
hasIconicMask
Indicates that an entity is associated with or characterized by a distinctive, widely recognized mask.
- 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_69f76ec654d48190b421111cf26e54d9 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdb0de8c08190928cd1323f80ab5c |
completed | May 7, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69fcd9017dd88190b32a73fe78909740 |
completed | May 7, 2026, 6:25 p.m. |
| PDg | Predicate description generation | batch_69fcdb0cf6008190b27046b694f84356 |
completed | May 7, 2026, 6:33 p.m. |
Created at: May 3, 2026, 4:32 p.m.