Triple
T35690323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dobšinská Ice Cave |
E1031268
|
entity |
| Predicate | iceVolume |
P98818
|
FINISHED |
| Object | approximately 110,000 m³ |
—
|
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: approximately 110,000 m³ | Statement: [Dobšinská Ice Cave, iceVolume, approximately 110,000 m³]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: iceVolume Context triple: [Dobšinská Ice Cave, iceVolume, approximately 110,000 m³]
-
A.
iceVolumeTrend
Indicates the direction and rate at which the volume of ice is changing over time.
-
B.
waterVolume
Indicates the amount of water present in or associated with an entity, typically measured as a volume.
-
C.
meanVolume_km3
Indicates the average volume of an entity, measured in cubic kilometers (km³), typically over a specified period or set of conditions.
-
D.
volumeOf
chosen
Indicates the quantitative three-dimensional space occupied by an entity or contained within an object.
-
E.
iceClass
Indicates a classification relationship specifying the level or category of ice-strengthening or ice-navigation capability assigned to a vessel or structure.
- 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_69f76e0c73ec819080ab60a9e2f5f1f6 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a34f8ee08190a040304635539a8f |
completed | May 3, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69f7a06f125c8190843af194f042a465 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:05 p.m.