Triple
T20085947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Petrohué Waterfalls |
E496127
|
entity |
| Predicate | approximateDistanceUnit |
P138665
|
FINISHED |
| Object | kilometres |
—
|
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: kilometres | Statement: [Petrohué Waterfalls, approximateDistanceUnit, kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateDistanceUnit Context triple: [Petrohué Waterfalls, approximateDistanceUnit, kilometres]
-
A.
approximateDistanceFrom
Indicates an estimated or rough measure of how far one entity is from another.
-
B.
distanceMeasurementMethod
Indicates the method or technique used to determine or measure the distance between entities.
-
C.
approximateLengthInMeters
Indicates the estimated or roughly measured length of something expressed in meters.
-
D.
hasApproximateDistanceScale
Indicates that one entity is related to another by a distance measure that is approximate or estimated rather than exact.
-
E.
depthApproxKm
Indicates the approximate depth of something measured in kilometers.
- F. None of above. chosen
Provenance (4 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_69da626eee3881909f3454986d4a6511 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6655ae9ec8190bde2f17452639de8 |
completed | April 20, 2026, 5:41 p.m. |
| PD | Predicate disambiguation | batch_69e54cf369b88190931532420517dac7 |
completed | April 19, 2026, 9:45 p.m. |
| PDg | Predicate description generation | batch_69e54fc20888819083c9118a09d0d2dc |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 11, 2026, 10:58 p.m.