Triple
T21248955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British–Irish Ice Sheet |
E523689
|
entity |
| Predicate | maximumThicknessApproximate |
P55323
|
FINISHED |
| Object | over 1,000 metres in some areas |
—
|
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: over 1,000 metres in some areas | Statement: [British–Irish Ice Sheet, maximumThicknessApproximate, over 1,000 metres in some areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumThicknessApproximate Context triple: [British–Irish Ice Sheet, maximumThicknessApproximate, over 1,000 metres in some areas]
-
A.
hasMaximumThickness
chosen
Indicates that an entity possesses a specified upper limit on its thickness.
-
B.
approximateMaximumHeight
Indicates the estimated upper limit of an entity’s height, rather than an exact measured value.
-
C.
armorThicknessMax
Indicates the maximum thickness of armor that an entity possesses or can withstand.
-
D.
maximumSurfaceArea
Indicates that one entity has the greatest possible surface area among a set of comparable entities or under specified conditions.
-
E.
typicalThicknessFormula
Indicates the standard or commonly used formula for calculating the thickness of something under typical conditions.
- 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_69e0b5146c108190adc9adb73e90abff |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7359c7a648190b4345336ac3be024 |
completed | April 21, 2026, 8:30 a.m. |
| PD | Predicate disambiguation | batch_69e5f61239708190ab7b3c83ae848a0d |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3:56 p.m.