Triple
T18420322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spanish Castle Magic |
E442003
|
entity |
| Predicate | hasStudioEffect |
P88203
|
FINISHED |
| Object | panning |
—
|
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: panning | Statement: [Spanish Castle Magic, hasStudioEffect, panning]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStudioEffect Context triple: [Spanish Castle Magic, hasStudioEffect, panning]
-
A.
hasStudio
Indicates that an entity (such as a film, game, or production) is associated with or produced by a particular studio.
-
B.
usesStudioEffects
chosen
Indicates that an entity incorporates studio-produced effects (such as audio or visual enhancements) in the creation or presentation of its work.
-
C.
usesStageEffects
Indicates that an entity employs stage-based visual, auditory, or mechanical effects as part of a performance or presentation.
-
D.
specialEffectsBy
Indicates that the special effects for something (such as a film, scene, or shot) are created or provided by a particular person or entity.
-
E.
hasEffectIn
Indicates that one entity produces, causes, or exerts an effect within a specified context, system, or environment.
- 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_69d8b9eb8a508190a942fd75ebd8b1dc |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e51a2b0f0481909c3995bf532162a3 |
completed | April 19, 2026, 6:08 p.m. |
| PD | Predicate disambiguation | batch_69e469bf7f74819096a01173493412c2 |
completed | April 19, 2026, 5:35 a.m. |
Created at: April 10, 2026, 10:47 a.m.