Triple
T2946554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Furtwängler Glacier |
E79515
|
entity |
| Predicate | thicknessTrend |
P5318
|
FINISHED |
| Object | decreasing |
—
|
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: decreasing | Statement: [Furtwängler Glacier, thicknessTrend, decreasing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thicknessTrend Context triple: [Furtwängler Glacier, thicknessTrend, decreasing]
-
A.
thickness
Indicates the measure of how deep or wide an object or layer is from one surface or side to its opposite.
-
B.
trends
Indicates that one entity exhibits a general direction of change or development over time in relation to another reference or context.
-
C.
styleTendsTo
Indicates that one style is generally inclined or likely to develop, appear, or be adopted in the direction of another style.
-
D.
hasTrend
chosen
Indicates that something exhibits or is associated with a particular pattern of change or direction over time.
-
E.
deckArmorThickness
Indicates the thickness of the armor plating on the horizontal deck surface of a vehicle, 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_69ad8b1089588190b74d9e2505e45762 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad98b3f86c819094526c2af611bfb5 |
completed | March 8, 2026, 3:41 p.m. |
| PD | Predicate disambiguation | batch_69ad960a70ac8190816b5ae3e8631031 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:56 p.m.