Triple
T30053969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Entrance of Zion National Park |
E763675
|
entity |
| Predicate | typicalTrafficLevel |
P145042
|
FINISHED |
| Object | high visitation |
—
|
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: high visitation | Statement: [South Entrance of Zion National Park, typicalTrafficLevel, high visitation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTrafficLevel Context triple: [South Entrance of Zion National Park, typicalTrafficLevel, high visitation]
-
A.
trafficLevel
Indicates the degree of congestion or flow intensity present in a transportation network or route at a given time.
-
B.
relativeTrafficLevel
Indicates the comparative intensity or volume of traffic between two or more locations, routes, or time periods.
-
C.
hasLevelOfTraffic
chosen
Indicates the degree or intensity of traffic present in or affecting a given entity or location.
-
D.
hasTransitTrafficLevel
Indicates the level or intensity of transit traffic associated with an entity, such as a road segment, route, or area.
-
E.
hasPedestrianTrafficLevel
Indicates the level or intensity of pedestrian traffic associated with a given location or pathway.
- 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_69f224716378819087a722e487832b70 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a03446ec72881909c5ff25a48baadb3 |
completed | May 12, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_6a03439b393c819084aa9b7ed0d5b6b0 |
completed | May 12, 2026, 3:13 p.m. |
Created at: April 29, 2026, 6:56 p.m.