Triple
T15216854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jostedalsbreen |
E363657
|
entity |
| Predicate | hasIceThickness |
P29933
|
FINISHED |
| Object | up to about 600 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: up to about 600 metres | Statement: [Jostedalsbreen, hasIceThickness, up to about 600 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIceThickness Context triple: [Jostedalsbreen, hasIceThickness, up to about 600 metres]
-
A.
typicalIceThickness
chosen
Indicates the usual or characteristic thickness of ice under normal or representative conditions.
-
B.
hasIceSurface
Indicates that an entity possesses or is characterized by a surface composed primarily of ice.
-
C.
hasIcebergs
Indicates that one entity (typically a body of water or region) contains or is characterized by the presence of icebergs.
-
D.
hasIceFront
Indicates that an entity possesses or is characterized by an ice-covered front or leading edge.
-
E.
hasSeaIce
Indicates that one entity possesses, contains, or is covered by sea ice in relation to another context or location.
- 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.