Triple
T2124999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elemental |
E46403
|
entity |
| Predicate | usesAnimationTechnique |
P3047
|
FINISHED |
| Object | computer 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: computer animation | Statement: [Elemental, usesAnimationTechnique, computer animation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesAnimationTechnique Context triple: [Elemental, usesAnimationTechnique, computer animation]
-
A.
hasTechnique
chosen
Indicates that an entity employs, utilizes, or is associated with a particular method, procedure, or technique.
-
B.
usesLightingFor
Indicates that one entity employs or relies on a particular lighting setup, technology, or condition to achieve a purpose or perform an action.
-
C.
usesElement
Indicates that one entity makes use of, incorporates, or depends on a specified element in its structure, function, or behavior.
-
D.
visualEffect
Indicates that one entity produces, modifies, or is associated with a particular visual effect on another entity or within a scene.
-
E.
isTechnical
Indicates that an entity possesses specialized technical knowledge, skills, or characteristics related to technology, engineering, or applied sciences.
- 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_69a88a1626548190ae59a5028c3baa8e |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abbb57bc6881909f04a407beff33a6 |
completed | March 7, 2026, 5:44 a.m. |
| PD | Predicate disambiguation | batch_69abb7bd86cc8190938ef06c1ed6d969 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:44 p.m.