Triple
T11739984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lambertian reflectance law |
E279125
|
entity |
| Predicate | idealizationOf |
P51621
|
FINISHED |
| Object | real diffuse surfaces |
—
|
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: real diffuse surfaces | Statement: [Lambertian reflectance law, idealizationOf, real diffuse surfaces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: idealizationOf Context triple: [Lambertian reflectance law, idealizationOf, real diffuse surfaces]
-
A.
hasIdealization
chosen
Indicates that one entity is a simplified, abstracted, or ideal form or model of another entity, capturing its essential features while omitting complexities.
-
B.
coreIdeal
Indicates that something is a fundamental, central principle or value that defines or strongly guides another entity.
-
C.
hasIdeal
Indicates that an entity holds or is associated with a guiding principle, standard, or value it considers perfect or most desirable.
-
D.
isPersonificationOf
Indicates that one entity represents or embodies an abstract concept, quality, or non-human thing in human form.
-
E.
rationalizationOf
Indicates that one entity serves as a justification, explanation, or reasoning framework for another entity, often making the latter appear more logical or acceptable.
- 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_69d6aaffec6881908bead509e8621742 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4f025f88190a39280806c9d7c33 |
completed | April 10, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69d88a813cc48190a3dfdc60e8af80ae |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:41 p.m.