Triple
T22549372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wingate Sandstone |
E557514
|
entity |
| Predicate | commonUses |
P144936
|
FINISHED |
| Object | scenic and recreational landscapes |
—
|
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: scenic and recreational landscapes | Statement: [Wingate Sandstone, commonUses, scenic and recreational landscapes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonUses Context triple: [Wingate Sandstone, commonUses, scenic and recreational landscapes]
-
A.
commonUseCategory
Indicates that multiple entities share the same general category of use or functional purpose.
-
B.
widelyUsedIn
Indicates that something is commonly or extensively utilized within a particular context, domain, or group.
-
C.
oftenUse
Indicates that one entity frequently or regularly uses, employs, or utilizes another entity.
-
D.
primaryUseOf
Indicates that one entity serves as the main or principal function, purpose, or application of another entity.
-
E.
frequentUseCase
chosen
Indicates a situation, scenario, or pattern of use that occurs regularly or more often than others in relation to the subject.
- 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_69e11e58662081909ae346ab384514ca |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15f74512c8190b5369e19a4bc6325 |
completed | April 29, 2026, 1:31 a.m. |
| PD | Predicate disambiguation | batch_69e898cb3fb48190add6ab24a2df5822 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:52 p.m.