Triple
T6040676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rwandan franc |
E134534
|
entity |
| Predicate | hasInflationRate |
P68325
|
FINISHED |
| Object | subject to Rwandan monetary policy |
—
|
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: subject to Rwandan monetary policy | Statement: [Rwandan franc, hasInflationRate, subject to Rwandan monetary policy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInflationRate Context triple: [Rwandan franc, hasInflationRate, subject to Rwandan monetary policy]
-
A.
hasInflation
Indicates that an economic system, currency, or market is experiencing a general increase in prices and a corresponding decrease in purchasing power over time.
-
B.
hasInflationRisk
Indicates that something is subject to potential loss of value or purchasing power due to inflation.
-
C.
hasInflationHistory
Indicates that an entity is associated with a recorded or known pattern of inflation over time.
-
D.
inflationRateAfter
Indicates the rate of inflation that applies following a specified time, event, or reference point.
-
E.
hasInflationTargetImplicit
Indicates that an entity maintains an inflation target that is not formally announced or explicitly stated, but is understood or inferred from its behavior or policies.
- 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_69c00875db5c819099dd5bb833ec43c2 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056cf82d481909d5161fe3643e7ed |
completed | March 22, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69c049eb52a08190ac10fd703735f5aa |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04e8d4a148190bd8f95caae978e1b |
completed | March 22, 2026, 8:18 p.m. |
Created at: March 22, 2026, 4:08 p.m.