Triple
T6758023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loughrigg Fell |
E154512
|
entity |
| Predicate | hasHighestPointElevationMetres |
P14507
|
FINISHED |
| Object | 335 |
—
|
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: 335 | Statement: [Loughrigg Fell, hasHighestPointElevationMetres, 335]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHighestPointElevationMetres Context triple: [Loughrigg Fell, hasHighestPointElevationMetres, 335]
-
A.
highestPoint
Indicates that one entity is the point with the greatest elevation or height relative to another entity or defined area.
-
B.
hasHighestPointType
Indicates that the highest point of an entity is of a specified type or category.
-
C.
highestElevationApprox
Indicates that an entity has an approximate value for the maximum elevation reached within its spatial or conceptual extent.
-
D.
areaPeak
Indicates that a specified location or region is the highest point (peak) within a given area or spatial extent.
-
E.
summitElevation
chosen
Indicates the elevation or height of a summit above a reference level, typically sea level.
- 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_69c6880fd5808190be684854081e27dd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d327e37081909d576e6eff9eec97 |
completed | March 27, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69c6d09227108190b253b91967831a85 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:11 p.m.