Triple
T19991528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indian economy |
E494075
|
entity |
| Predicate | incomeCategory |
P24934
|
FINISHED |
| Object | lower-middle-income country |
—
|
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: lower-middle-income country | Statement: [Indian economy, incomeCategory, lower-middle-income country]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: incomeCategory Context triple: [Indian economy, incomeCategory, lower-middle-income country]
-
A.
incomeType
chosen
Indicates the category or source classification of an entity’s income within a given context.
-
B.
incomeUsedFor
Indicates that some or all of an income amount is allocated or spent for a specified purpose, activity, or recipient.
-
C.
income
Indicates the amount of money an entity receives, typically over a specified period, from work, investments, or other sources.
-
D.
payCategory
Indicates the classification of a payment or compensation into a specific category (such as type, purpose, or pay band) within a payment or payroll context.
-
E.
mainExpenditureCategory
Indicates the primary type or classification of spending to which a particular expenditure mainly belongs.
- 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_69da626a67648190af9653832a3aeced |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65fe00b908190bda6b9a3a3281ec0 |
completed | April 20, 2026, 5:18 p.m. |
| PD | Predicate disambiguation | batch_69e537fd311881908448f2aea8b4812e |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 11, 2026, 3:31 p.m.