Triple
T37769121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Potion of Regeneration |
E941491
|
entity |
| Predicate | iconEffect |
P30078
|
FINISHED |
| Object | Regeneration status icon |
—
|
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: Regeneration status icon | Statement: [Potion of Regeneration, iconEffect, Regeneration status icon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: iconEffect Context triple: [Potion of Regeneration, iconEffect, Regeneration status icon]
-
A.
iconOf
chosen
Indicates that one entity serves as a symbolic or representative image or emblem of another entity.
-
B.
visualEffect
Indicates that one entity produces, modifies, or is associated with a particular visual effect on another entity or within a scene.
-
C.
maskEffect
Indicates that one entity serves to conceal, obscure, or alter the apparent effect or influence of another.
-
D.
arrowEffect
Indicates that one entity causes or produces a directional influence or outcome on another, similar to an arrow showing the effect from source to target.
-
E.
showsEffect
Indicates that one entity produces, demonstrates, or reveals a particular effect or outcome on another entity or context.
- 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_69f76ee3251881909bb4451aad50752b |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbaf1c5a588190b213d1a22511e298 |
completed | May 6, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69fbadf632ec8190b14991c971258307 |
completed | May 6, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:19 p.m.