Triple
T29072575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hawaiian dollar |
E735848
|
entity |
| Predicate | designModeledOn |
P185164
|
FINISHED |
| Object | United States dollar |
—
|
NE NERFINISHED |
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: United States dollar | Statement: [Hawaiian dollar, designModeledOn, United States dollar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: designModeledOn Context triple: [Hawaiian dollar, designModeledOn, United States dollar]
-
A.
designModel
Indicates that one entity creates, specifies, or defines the structure or behavior of another entity as a model or blueprint.
-
B.
systemModeledOn
chosen
Indicates that one system is designed, structured, or conceptualized based on the principles, structure, or behavior of another system.
-
C.
modeledWith
Indicates that something is represented, simulated, or described using a particular model, method, or modeling technique.
-
D.
usesDesignModel
Indicates that one entity applies or relies on a particular design model in performing its function or defining its structure.
-
E.
modelIn
Indicates that one entity serves as a representation or simulation of another entity.
- 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_69f077e9b0a48190bb79548279cb7f64 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69fbaebc8f2c8190b94f1b4a3ec92e8c |
completed | May 6, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69fbadf1e6008190a71bbd196ba06844 |
completed | May 6, 2026, 9:09 p.m. |
Created at: April 28, 2026, 10:20 a.m.