Triple
T7734137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bright Angel Point |
E175337
|
entity |
| Predicate | hasFacilityNearby |
P5648
|
FINISHED |
| Object | parking area at North Rim visitor services |
—
|
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: parking area at North Rim visitor services | Statement: [Bright Angel Point, hasFacilityNearby, parking area at North Rim visitor services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFacilityNearby Context triple: [Bright Angel Point, hasFacilityNearby, parking area at North Rim visitor services]
-
A.
hasNearbyFacility
chosen
Indicates that one entity is located close to or in the vicinity of a particular facility.
-
B.
nearbyFacilityType
Indicates that a facility of a specified type is located close to a given reference entity or location.
-
C.
hasAttractionNearby
Indicates that one entity is located close to another entity that serves as an attraction or point of interest.
-
D.
hasNearbyInstitution
Indicates that one entity is located close to or in the immediate vicinity of an institution.
-
E.
hasFacilities
Indicates that an entity possesses, provides, or is equipped with certain facilities or physical resources.
- 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_69c6995e912c81909a49a2657103f786 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c70402169481909b219dc5f4a64b9b |
completed | March 27, 2026, 10:26 p.m. |
| PD | Predicate disambiguation | batch_69c7016c4a748190a7012030edaefcee |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:06 p.m.