Triple
T16516452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Columbia Icefield |
E401196
|
entity |
| Predicate | thicknessMax |
P55323
|
FINISHED |
| Object | up to about 365 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: up to about 365 meters | Statement: [Columbia Icefield, thicknessMax, up to about 365 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thicknessMax Context triple: [Columbia Icefield, thicknessMax, up to about 365 meters]
-
A.
thickness
Indicates the measure of how deep or wide an object or layer is from one surface or side to its opposite.
-
B.
hasMaximumThickness
chosen
Indicates that an entity possesses a specified upper limit on its thickness.
-
C.
armorThicknessMax
Indicates the maximum thickness of armor that an entity possesses or can withstand.
-
D.
thickestIn
Indicates that one entity has the greatest thickness among a specified set or within a given context.
-
E.
bodyThickness
Indicates the measured or relative thickness of an entity’s body in the context of a comparison or description.
- 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e7c7e588190acbcc2b807a98909 |
completed | April 18, 2026, 7:10 a.m. |
| PD | Predicate disambiguation | batch_69e296995d388190b88ebe189dce890d |
completed | April 17, 2026, 8:22 p.m. |
Created at: April 10, 2026, 5:14 a.m.