Triple
T21248975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British–Irish Ice Sheet |
E523689
|
entity |
| Predicate | modelledUsing |
P113729
|
FINISHED |
| Object | ice-sheet models |
—
|
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: ice-sheet models | Statement: [British–Irish Ice Sheet, modelledUsing, ice-sheet models]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modelledUsing Context triple: [British–Irish Ice Sheet, modelledUsing, ice-sheet models]
-
A.
modeledWith
chosen
Indicates that something is represented, simulated, or described using a particular model, method, or modeling technique.
-
B.
usedByModel
Indicates that something (such as a resource, method, or component) is utilized or consumed by a particular model.
-
C.
useOfModel
Indicates that one entity employs, applies, or relies on a particular model for a specific purpose or task.
-
D.
usesModelsType
Indicates that one entity employs or relies on a specific type or category of models in its operation or behavior.
-
E.
hasModelledFor
Indicates that one entity has served as a model for another entity, typically in a professional or representational context such as art, photography, or fashion.
- 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.