Triple
T15489247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Ngungun |
E377134
|
entity |
| Predicate | hasApproxTrailLength_km |
P69216
|
FINISHED |
| Object | 2.8 |
—
|
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: 2.8 | Statement: [Mount Ngungun, hasApproxTrailLength_km, 2.8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproxTrailLength_km Context triple: [Mount Ngungun, hasApproxTrailLength_km, 2.8]
-
A.
trailLengthApprox
Indicates an approximate measurement of the total length of a trail.
-
B.
trackLengthApproxKm
chosen
Indicates that one entity has an approximate track length, measured in kilometers, associated with it.
-
C.
trailDistanceApprox
Indicates that the distance along a trail between two locations is approximately a specified value, allowing for some margin of error.
-
D.
navigableLengthApproxKm
Indicates the approximate distance, measured in kilometers, over which something (typically a waterway) can be navigated.
-
E.
lengthInKm
Indicates that one entity specifies the length or distance of another entity measured in kilometers.
- 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_69d85cd21dcc81908646251b1c26ea00 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03faaca588190b0397bc2e27a522a |
completed | April 16, 2026, 1:47 a.m. |
| PD | Predicate disambiguation | batch_69ded2874b788190999158e0f043be21 |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:48 a.m.