Triple
T4437560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mauna Kea Science Reserve |
E95687
|
entity |
| Predicate | hasAltitudeRange |
P1977
|
FINISHED |
| Object | approximately 3700 to 4200 meters |
—
|
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: approximately 3700 to 4200 meters | Statement: [Mauna Kea Science Reserve, hasAltitudeRange, approximately 3700 to 4200 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAltitudeRange Context triple: [Mauna Kea Science Reserve, hasAltitudeRange, approximately 3700 to 4200 meters]
-
A.
hasAltitudeFeature
Indicates that an entity possesses a characteristic or attribute related to its elevation or vertical position above a reference level.
-
B.
hasAltitudeStation
Indicates that something is associated with or located at a station characterized by a specific altitude.
-
C.
typicalElevationRange
chosen
Indicates the usual range of elevation values within which something commonly occurs or exists.
-
D.
hasAreaRange
Indicates that something’s area falls within a specified minimum-to-maximum range.
-
E.
locatedAtAltitude
Indicates that an entity exists or is positioned at a specific height above a reference level, typically sea level.
- 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_69b3453ea2b48190a26f154b3b8fece5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3558b1d4481909060ede5e0ded4bc |
completed | March 13, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69b34f6078cc8190831b89f404198cc5 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:31 p.m.