Triple
T38330869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Face Standard Route |
E1037817
|
entity |
| Predicate | onHighestPeakOf |
P190429
|
FINISHED |
| Object | Mount Kenya |
—
|
NE NERFINISHED |
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: Mount Kenya | Statement: [North Face Standard Route, onHighestPeakOf, Mount Kenya]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: onHighestPeakOf Context triple: [North Face Standard Route, onHighestPeakOf, Mount Kenya]
-
A.
nearHighestPeakOf
Indicates that one entity is located close to the highest peak of another referenced geographic or topographic feature.
-
B.
hasHighestPeakName
Indicates that the related value is the name of the tallest peak associated with the given entity.
-
C.
countryHighestPeak
Indicates that a given peak is the tallest mountain within the specified country.
-
D.
isMostFamousPeakOf
Indicates that one peak is recognized as the most famous or well-known peak associated with a particular geographic area, range, or entity.
-
E.
containsHighestPointOf
Indicates that one entity includes within its boundaries the location of the highest point of another entity.
- 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_69f76e20d65c81909619ac0dd85c56f0 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fcc7a4d7f881908b43b960911b81e9 |
completed | May 7, 2026, 5:11 p.m. |
| PD | Predicate disambiguation | batch_69fcc589720c819089c8f500fea3c86a |
completed | May 7, 2026, 5:02 p.m. |
| PDg | Predicate description generation | batch_69fcc7a42f68819081d6ec8bb6b53438 |
completed | May 7, 2026, 5:11 p.m. |
Created at: May 3, 2026, 4:30 p.m.