Triple
T3855315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panamanian balboa |
E89998
|
entity |
| Predicate | pegRate |
P52365
|
FINISHED |
| Object | 1 balboa = 1 United States dollar |
—
|
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: 1 balboa = 1 United States dollar | Statement: [Panamanian balboa, pegRate, 1 balboa = 1 United States dollar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pegRate Context triple: [Panamanian balboa, pegRate, 1 balboa = 1 United States dollar]
-
A.
pegRatio
Indicates the relationship between a company’s price-to-earnings (P/E) ratio and its expected earnings growth rate, expressing how highly the market values each unit of anticipated growth.
-
B.
maximumBitrate
Indicates the highest data transfer rate allowed or supported for a given media stream or connection.
-
C.
dataRate
Indicates the rate at which data is transmitted, processed, or transferred between entities over a given time interval.
-
D.
pegType
Indicates the specific category or kind of peg associated with or assigned to an entity.
-
E.
typicalResolution
Indicates the usual or standard level of detail or clarity at which something (such as an image, display, or representation) is normally rendered or presented.
- F. None of above. chosen
Provenance (4 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_69aed95b3c088190a8f85d19e6070599 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec05ec4c8190bd5e5463163712dc |
completed | March 9, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69aee752c8a48190a670f73ed0bf1e61 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aeeb828fb08190901d51edbe8bd304 |
completed | March 9, 2026, 3:47 p.m. |
Created at: March 9, 2026, 3:19 p.m.