Triple
T38593365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caduceus Blaster |
E932504
|
entity |
| Predicate | equippedWhen |
P191266
|
FINISHED |
| Object | Mercy is not using Caduceus Staff |
—
|
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: Mercy is not using Caduceus Staff | Statement: [Caduceus Blaster, equippedWhen, Mercy is not using Caduceus Staff]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: equippedWhen Context triple: [Caduceus Blaster, equippedWhen, Mercy is not using Caduceus Staff]
-
A.
equippedFor
Indicates that one entity is suitably provided with the necessary tools, features, or capabilities to perform a particular function or handle a specific situation for another entity or purpose.
-
B.
usesEquipment
Indicates that an entity employs or operates a particular piece of equipment to perform an action or fulfill a function.
-
C.
oftenEquippedWith
Indicates that one type of entity is frequently or typically outfitted, furnished, or supplied with another entity.
-
D.
woreEquipment
Indicates that an entity used or had on their person a specific piece of equipment.
-
E.
equipmentIncludes
Indicates that one entity contains, comprises, or has as part of its set of items a specified piece or set of equipment.
- 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.