Triple
T20597379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Whitefish Lake |
E506083
|
entity |
| Predicate | hasNearbyCityPopulationCategory |
P65946
|
FINISHED |
| Object | small resort town |
—
|
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: small resort town | Statement: [Whitefish Lake, hasNearbyCityPopulationCategory, small resort town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyCityPopulationCategory Context triple: [Whitefish Lake, hasNearbyCityPopulationCategory, small resort town]
-
A.
hasNearbyCityArea
Indicates that one area is geographically close to or adjacent to a city area.
-
B.
hasNearbyCityFunction
Indicates that one entity serves as a nearby urban center or city-like service hub for another entity.
-
C.
hasNearbyMajorCityCountry
Indicates that an entity has a nearby major city located in the specified country.
-
D.
hasNearbyUSCity
Indicates that one location has at least one city in the United States situated within a specified nearby distance.
-
E.
hasNearbyTownType
chosen
Indicates that one entity has, in its vicinity, a town of a specified type or classification.
- 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_69e0b4ba6ae88190af871e1f9522c704 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aa1d15b08190a720fc7cefbf333e |
completed | April 20, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69e59fffe1748190825e4eaa90340631 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:40 a.m.