Triple
T11660261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | End City |
E277100
|
entity |
| Predicate | hasStatusEffectSource |
P100843
|
FINISHED |
| Object | Levitation from shulker projectiles |
—
|
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: Levitation from shulker projectiles | Statement: [End City, hasStatusEffectSource, Levitation from shulker projectiles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStatusEffectSource Context triple: [End City, hasStatusEffectSource, Levitation from shulker projectiles]
-
A.
hasTypeOfEffect
Indicates that one entity produces, exhibits, or is associated with a particular kind or category of effect on another entity or context.
-
B.
usesEffectType
Indicates that an entity employs or is associated with a particular type or category of effect in its operation or behavior.
-
C.
hasIntendedEffect
Indicates that one entity is expected or designed to produce a particular effect or outcome on another entity or context.
-
D.
hasEffectNamedAfter
Indicates that an entity has an effect or phenomenon that is named after another entity.
-
E.
isQuantumEffect
Indicates that the relationship or phenomenon arises specifically from quantum mechanical principles or effects rather than classical behavior.
- 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_69d6aafbb3c081908a9cdb4ecb8d981d |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a3d19c788190826d849a6ffedc72 |
completed | April 10, 2026, 7:16 a.m. |
| PD | Predicate disambiguation | batch_69d88a73f9ac819095662042804bf40a |
completed | April 10, 2026, 5:28 a.m. |
| PDg | Predicate description generation | batch_69d890458d948190b15054c9ba0fd923 |
completed | April 10, 2026, 5:53 a.m. |
Created at: April 8, 2026, 9:39 p.m.