Triple
T17922085
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ICE clearing network |
E448097
|
entity |
| Predicate | usesClearingModel |
P107384
|
FINISHED |
| Object | central counterparty model |
—
|
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: central counterparty model | Statement: [ICE clearing network, usesClearingModel, central counterparty model]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesClearingModel Context triple: [ICE clearing network, usesClearingModel, central counterparty model]
-
A.
clearingSystem
Indicates that one entity functions as the financial clearing mechanism or infrastructure used to settle transactions for another entity.
-
B.
usesModelsType
chosen
Indicates that one entity employs or relies on a specific type or category of models in its operation or behavior.
-
C.
usesAcquisitionModel
Indicates that one entity employs or applies a particular acquisition model as the method or framework for obtaining something.
-
D.
scopeModelUsed
Indicates that a particular model is employed or applied within a specified scope or context.
-
E.
notUsedOnModel
Indicates that a particular item, component, or feature is not applied, installed, or utilized on the specified model.
- 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4a30ad8748190b28d3e8b5afab2ef |
completed | April 19, 2026, 9:40 a.m. |
| PD | Predicate disambiguation | batch_69e3d8ec2f6881909d7f54b878cbed37 |
completed | April 18, 2026, 7:18 p.m. |
Created at: April 10, 2026, 10:20 a.m.