Triple
T4766563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Income Doubling Plan |
E105825
|
entity |
| Predicate | targetGrowthRate |
P29162
|
FINISHED |
| Object | approximately 7 percent per year or higher |
—
|
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: approximately 7 percent per year or higher | Statement: [Income Doubling Plan, targetGrowthRate, approximately 7 percent per year or higher]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetGrowthRate Context triple: [Income Doubling Plan, targetGrowthRate, approximately 7 percent per year or higher]
-
A.
hasGrowthRate
chosen
Indicates the rate at which something increases in size, quantity, or value over a given period of time.
-
B.
targetInflationRate
Indicates the inflation level that a monetary authority aims to achieve and maintain over a specified period.
-
C.
growthProperty
Indicates that one entity characterizes, constrains, or quantifies how another entity grows or changes in magnitude over some parameter (such as time, size, or input).
-
D.
growthType
Indicates the manner or pattern in which something develops or increases over time.
-
E.
growthPolicy
Indicates a rule or strategy that governs how something is allowed or expected to grow or expand over time.
- 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_69bd43f226fc8190b867cc249c2a9042 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd686ef1b08190ad60375592c9d6c0 |
completed | March 20, 2026, 3:31 p.m. |
| PD | Predicate disambiguation | batch_69bd622807f881908e4bcb14f7731bac |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:21 p.m.