Triple
T5224551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Earth vs. the Flying Saucers |
E117952
|
entity |
| Predicate | visualEffectsTechnique |
P51617
|
FINISHED |
| Object | stop-motion animation |
—
|
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: stop-motion animation | Statement: [Earth vs. the Flying Saucers, visualEffectsTechnique, stop-motion animation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visualEffectsTechnique Context triple: [Earth vs. the Flying Saucers, visualEffectsTechnique, stop-motion animation]
-
A.
visualEffect
Indicates that one entity produces, modifies, or is associated with a particular visual effect on another entity or within a scene.
-
B.
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.
-
C.
specialEffectsPioneer
Indicates that the subject is recognized for groundbreaking or innovative work in the field of special effects.
-
D.
featuresTechnique
chosen
Indicates that something incorporates or makes use of a particular technique as part of its content or execution.
-
E.
filmingTechnique
Indicates the specific method or style used to capture visual content during the filming process.
- 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_69bd4465e03081909bfcfd7113062590 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7abd3ed48190bfd8d2f2ca399741 |
completed | March 20, 2026, 4:50 p.m. |
| PD | Predicate disambiguation | batch_69bd77bd2a448190a9ae5afd2585a7b9 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:48 p.m.