Triple
T2793610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Tenkiller area |
E61983
|
entity |
| Predicate | hasCampingFacilityType |
P10334
|
FINISHED |
| Object | campgrounds |
—
|
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: campgrounds | Statement: [Lake Tenkiller area, hasCampingFacilityType, campgrounds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCampingFacilityType Context triple: [Lake Tenkiller area, hasCampingFacilityType, campgrounds]
-
A.
hasCampground
Indicates that one entity provides, contains, or is associated with a campground facility or area for another entity.
-
B.
hasNumberOfCampsites
Indicates the specific quantity of campsites associated with a given place, facility, or area.
-
C.
trainingCampSite
Indicates that a location serves as the site where training camps are held or conducted.
-
D.
hasCampType
chosen
Indicates that an entity is associated with or classified by a particular type or category of camp.
-
E.
hasCabins
Indicates that an entity possesses or includes one or more cabins as part of its structure or facilities.
- 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_69ab4b7f51d881908768300ebd2fbdae |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abddd33610819085ac7c5bec0e6af0 |
completed | March 7, 2026, 8:12 a.m. |
| PD | Predicate disambiguation | batch_69abdd040f9481908e9c7a2df88ea1ae |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:58 p.m.