Triple
T15217101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kjølen Mountains |
E363663
|
entity |
| Predicate | hasHighestPointInSection |
P210
|
FINISHED |
| Object | various peaks over 1,000 metres |
—
|
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: various peaks over 1,000 metres | Statement: [Kjølen Mountains, hasHighestPointInSection, various peaks over 1,000 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHighestPointInSection Context triple: [Kjølen Mountains, hasHighestPointInSection, various peaks over 1,000 metres]
-
A.
hasHighest
Indicates that one entity possesses the greatest value, rank, or level in a specified attribute or set compared to all others.
-
B.
hasHighestPointType
Indicates that the highest point of an entity is of a specified type or category.
-
C.
highestSectionsLocatedIn
Indicates that the highest parts or sections of an entity are situated within a specified location or area.
-
D.
hasHighestStructure
Indicates that an entity possesses the tallest or most elevated structural feature compared to all other relevant entities in a given context.
-
E.
highestPoint
chosen
Indicates that one entity is the point with the greatest elevation or height relative to another entity or defined area.
- 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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0076f90c481909989befe031a2cae |
completed | April 15, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69deca8479188190b2e5d3bc708d7d07 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:11 a.m.