Triple
T4063848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Wolfman (2010 film) |
E86277
|
entity |
| Predicate | specialEffectsType |
P37149
|
FINISHED |
| Object | werewolf transformation effects |
—
|
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: werewolf transformation effects | Statement: [The Wolfman (2010 film), specialEffectsType, werewolf transformation effects]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: specialEffectsType Context triple: [The Wolfman (2010 film), specialEffectsType, werewolf transformation effects]
-
A.
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.
-
B.
visualEffect
Indicates that one entity produces, modifies, or is associated with a particular visual effect on another entity or within a scene.
-
C.
specialEffectsPioneer
Indicates that the subject is recognized for groundbreaking or innovative work in the field of special effects.
-
D.
specialAppearance
Indicates that an entity makes a notable or exceptional appearance distinct from its usual or regular presence.
-
E.
usesEffectType
chosen
Indicates that an entity employs or is associated with a particular type or category of effect in its operation or behavior.
- 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_69aed93c69208190a4efac0efe3cd69b |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefd0bdea48190805a79515ee92709 |
completed | March 9, 2026, 5:02 p.m. |
| PD | Predicate disambiguation | batch_69aef90438908190a005b08ba271eacf |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:38 p.m.