Triple
T3158760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peruvian economy |
E66053
|
entity |
| Predicate | incomeClassification |
P3066
|
FINISHED |
| Object | upper-middle-income economy |
—
|
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: upper-middle-income economy | Statement: [Peruvian economy, incomeClassification, upper-middle-income economy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: incomeClassification Context triple: [Peruvian economy, incomeClassification, upper-middle-income economy]
-
A.
incomeType
Indicates the category or source classification of an entity’s income within a given context.
-
B.
economicClassification
chosen
Indicates how an entity is categorized based on its economic characteristics, status, or role within an economic system.
-
C.
economicStatus
Indicates the financial or socioeconomic condition or standing of an entity relative to others or to defined economic criteria.
-
D.
socialClassSystem
Indicates a hierarchical organization of people into social classes based on status, power, or economic position.
-
E.
incomeTreatment
Indicates a relationship where an entity receives, is subject to, or is affected by a particular income-related treatment, policy, or classification.
- 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_69ad85850c1481908a9e9c6242238de2 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada5ed82a08190a1bdcf18ee593c79 |
completed | March 8, 2026, 4:38 p.m. |
| PD | Predicate disambiguation | batch_69ad9dfbf0348190952a6bca8fc5fed1 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:05 p.m.