Triple
T37860623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phong reflection model |
E944314
|
entity |
| Predicate | ambientTermDependsOn |
P189291
|
FINISHED |
| Object | ambient light intensity |
—
|
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: ambient light intensity | Statement: [Phong reflection model, ambientTermDependsOn, ambient light intensity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ambientTermDependsOn Context triple: [Phong reflection model, ambientTermDependsOn, ambient light intensity]
-
A.
entropyTermDependsOn
Indicates that the value of an entropy term is functionally dependent on another specified quantity or set of variables.
-
B.
ambientSpace
Indicates the surrounding or containing space within which an object, structure, or geometric entity is situated or defined.
-
C.
premierTermDependentOn
Indicates that the validity, duration, or conditions of a premier term are contingent upon another specified factor, agreement, or event.
-
D.
environs
Indicates that one entity surrounds, encircles, or lies all around another entity in space.
-
E.
positionDependsOn
Indicates that the spatial or ordered position of one entity is determined or constrained by the position of another entity.
- 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_69f76eee2f9c8190b1272aa2ee55ebf5 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbbae559a8819086ef839973f8d9b2 |
completed | May 6, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69fbb1440fa08190abf25ba684f75b6e |
completed | May 6, 2026, 9:23 p.m. |
| PDg | Predicate description generation | batch_69fbbae3fc508190adff3d7abbf107a4 |
completed | May 6, 2026, 10:04 p.m. |
Created at: May 3, 2026, 4:19 p.m.