Triple
T30236959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smoke Hole, West Virginia |
E768796
|
entity |
| Predicate | closestNaturalFeature |
P73654
|
FINISHED |
| Object | Smoke Hole Canyon |
—
|
NE NERFINISHED |
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: Smoke Hole Canyon | Statement: [Smoke Hole, West Virginia, closestNaturalFeature, Smoke Hole Canyon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: closestNaturalFeature Context triple: [Smoke Hole, West Virginia, closestNaturalFeature, Smoke Hole Canyon]
-
A.
followsNaturalFeature
Indicates that one entity’s position, path, or boundary runs alongside or is aligned with a natural geographic feature (such as a river, coastline, or ridgeline).
-
B.
nearNaturalRegion
chosen
Indicates that one entity is located close to a specified natural region or area in geographic space.
-
C.
nearestLandmass
Indicates that one landmass is the closest geographically to another specified point or landmass.
-
D.
nearestMajorAttraction
Indicates the closest significant point of interest or landmark relative to a given location.
-
E.
nearestCityTo
Indicates that one city is the closest in distance to a given location or entity compared to all other cities.
- 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_69f224820c048190b1435c4cc145acf1 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f7465687bc8190a9da44d62b634ed7 |
completed | May 3, 2026, 12:57 p.m. |
| PD | Predicate disambiguation | batch_69f743f4ceb08190a21fe7f4a99b166b |
completed | May 3, 2026, 12:47 p.m. |
Created at: April 29, 2026, 7:37 p.m.