Triple
T9740102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | REYES architecture |
E236164
|
entity |
| Predicate | shadingGranularity |
P90441
|
FINISHED |
| Object | micropolygon vertices |
—
|
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: micropolygon vertices | Statement: [REYES architecture, shadingGranularity, micropolygon vertices]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shadingGranularity Context triple: [REYES architecture, shadingGranularity, micropolygon vertices]
-
A.
controlGranularity
Indicates the level of detail or fineness with which control or regulation is applied within a given process or system.
-
B.
grainSize
Indicates the relative coarseness or fineness of the material or particles involved in the relationship.
-
C.
shaded
Indicates that one entity partially or fully blocks light from reaching another, resulting in the latter being in shadow.
-
D.
reservationGranularity
Indicates the level of detail or unit (such as time, quantity, or capacity) at which a reservation can be specified or managed.
-
E.
encryptionGranularity
Indicates the level of detail or scope at which data is encrypted within a system or process.
- 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_69ca84d313e88190983ee6ffd0ef60d2 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9f29a5bc8190b2b391017405c71e |
completed | April 1, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69cd03cc128c81908b84ef224f858b4e |
completed | April 1, 2026, 11:38 a.m. |
| PDg | Predicate description generation | batch_69cd06aa8bc88190904be19c8953def8 |
completed | April 1, 2026, 11:51 a.m. |
Created at: March 30, 2026, 8:22 p.m.