Triple
T30036146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kalkaska sand |
E763162
|
entity |
| Predicate | typicalSlopeRange |
P144719
|
FINISHED |
| Object | 0 to 70 percent |
—
|
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: 0 to 70 percent | Statement: [Kalkaska sand, typicalSlopeRange, 0 to 70 percent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSlopeRange Context triple: [Kalkaska sand, typicalSlopeRange, 0 to 70 percent]
-
A.
hasSlopeRating
Indicates that something (typically a golf course or hole) is associated with a specific slope rating value that quantifies its relative difficulty for bogey golfers compared to scratch golfers.
-
B.
slopeType
Indicates the classification of a slope based on its geometric or physical characteristics, such as steepness, shape, or orientation.
-
C.
slopeAngleRange
chosen
Indicates the range of possible or allowed slope angles associated with a given entity or context.
-
D.
typicalRange
Indicates the usual or expected range of values, conditions, or states within which something normally occurs or applies.
-
E.
typicalElevationRange
Indicates the usual range of elevation values within which something commonly occurs or exists.
- 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_69f2246fb2b88190acff36bf7975c8f0 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a033d975d788190aafc4be10d6c5c1c |
completed | May 12, 2026, 2:47 p.m. |
| PD | Predicate disambiguation | batch_6a033cc2668481908cb696e57632a68f |
completed | May 12, 2026, 2:44 p.m. |
Created at: April 29, 2026, 6:51 p.m.