Triple
T1127314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Patagonian Ice Field |
E24748
|
entity |
| Predicate | surfaceAreaApprox |
P11494
|
FINISHED |
| Object | about 12,000 square kilometers |
—
|
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: about 12,000 square kilometers | Statement: [Southern Patagonian Ice Field, surfaceAreaApprox, about 12,000 square kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: surfaceAreaApprox Context triple: [Southern Patagonian Ice Field, surfaceAreaApprox, about 12,000 square kilometers]
-
A.
areaApprox
chosen
Indicates that one entity’s area is approximately equal to the area of another entity.
-
B.
approximateRadius
Indicates that one entity specifies or provides an estimated value for the radius of another entity.
-
C.
areaPeakApprox
Indicates an approximate measurement or estimation of the peak area associated with an entity or event.
-
D.
approximates
Indicates that one entity is close to, but not exactly equal to, the value, form, or behavior of another entity.
-
E.
approximateMass
Indicates that one entity has a mass value that is an estimate or close approximation of the mass of another entity.
- 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_69a4940712c88190aa244f3fc6070a65 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bc4bc21881909dcfe628f59f3e8c |
completed | March 1, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69a4bb48de2081909a0dce005b1c9df1 |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:44 p.m.