Triple
T37661799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nether Star |
E937733
|
entity |
| Predicate | associatedStatusEffects |
P100810
|
FINISHED |
| Object | Speed |
—
|
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: Speed | Statement: [Nether Star, associatedStatusEffects, Speed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedStatusEffects Context triple: [Nether Star, associatedStatusEffects, Speed]
-
A.
hasSecondaryEffect
Indicates that an action, event, or primary effect produces an additional, indirect, or consequential effect beyond its main intended outcome.
-
B.
hasEffectIn
Indicates that one entity produces, causes, or exerts an effect within a specified context, system, or environment.
-
C.
grantsStatusEffect
chosen
Indicates that one entity applies or bestows a specific status effect onto another entity.
-
D.
effectCount
Indicates the number of distinct effects or outcomes associated with a given action, event, or entity.
-
E.
specialEffect
Indicates that one entity produces, applies, or is associated with a distinctive, often non-standard effect on another entity or on an event.
- 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_69f76ed6df7c8190b018e5baea716ceb |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1772e48190ba738c6d11b321e2 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:18 p.m.