Triple
T8275749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colter Bay Visitor Center |
E193541
|
entity |
| Predicate | hasRangerPresence |
P13931
|
FINISHED |
| Object | park rangers on duty |
—
|
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: park rangers on duty | Statement: [Colter Bay Visitor Center, hasRangerPresence, park rangers on duty]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRangerPresence Context triple: [Colter Bay Visitor Center, hasRangerPresence, park rangers on duty]
-
A.
hasRangerDistrict
Indicates that an entity is associated with, managed by, or located within a specific ranger district.
-
B.
hasHumanPresence
chosen
Indicates that humans are physically present in or occupying a given location, object, or context.
-
C.
hasWarden
Indicates that one entity serves as the warden or supervisory authority responsible for another entity.
-
D.
hasCharacterPresence
Indicates that a particular character appears or is present within a specified context, such as a scene, work, or medium.
-
E.
hasMilitaryPresence
Indicates that a military force is present in, stationed at, or operating within a particular location or entity.
- 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_69ca82e14ae481908ffdb822cd2192bc |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb798d69508190b581ad8a38730175 |
completed | March 31, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69cb70a4525481909399d313a6247ace |
completed | March 31, 2026, 6:58 a.m. |
Created at: March 30, 2026, 5:51 p.m.