Triple
T14557648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Shining Pyramid |
E341584
|
entity |
| Predicate | slopeAngleUpperSection |
P114675
|
FINISHED |
| Object | about 43 degrees |
—
|
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: about 43 degrees | Statement: [Southern Shining Pyramid, slopeAngleUpperSection, about 43 degrees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: slopeAngleUpperSection Context triple: [Southern Shining Pyramid, slopeAngleUpperSection, about 43 degrees]
-
A.
slopeAspect
Indicates the compass direction that a slope or surface is facing.
-
B.
lowerInclinationAngle
Indicates that one entity has a smaller or more downward-tilted inclination angle compared to another entity.
-
C.
angleOfIncident
Indicates the angle at which one entity (such as a ray, line, or object) strikes or approaches the surface or boundary of another entity.
-
D.
leanAngle
Indicates the degree to which an entity is tilted or inclined away from a reference upright position.
-
E.
slopeType
Indicates the classification of a slope based on its geometric or physical characteristics, such as steepness, shape, or orientation.
- 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_69d822db9c8481908213ceb39585f792 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb3881b788190922932fb8ff81160 |
completed | April 14, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69de5c57489c8190b57917be1dba6ae6 |
completed | April 14, 2026, 3:25 p.m. |
| PDg | Predicate description generation | batch_69de5fb5ac548190932f238e37271741 |
completed | April 14, 2026, 3:39 p.m. |
Created at: April 10, 2026, 1:23 a.m.