Triple
T1808132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Microloan Program |
E40267
|
entity |
| Predicate | typicalLoanAmountRangeUSD |
P13474
|
FINISHED |
| Object | 13000 |
—
|
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: 13000 | Statement: [Microloan Program, typicalLoanAmountRangeUSD, 13000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalLoanAmountRangeUSD Context triple: [Microloan Program, typicalLoanAmountRangeUSD, 13000]
-
A.
loanLimitType
Indicates the category or rule that defines how a loan’s maximum allowable amount or terms are limited.
-
B.
typicalRange
chosen
Indicates the usual or expected range of values, conditions, or states within which something normally occurs or applies.
-
C.
typicalInvestmentSize
Indicates the usual or most common amount of money invested in a single investment or deal.
-
D.
loanType
Indicates the specific category or kind of loan associated with an entity or transaction.
-
E.
typicalAwardAmount
Indicates the usual or most common amount of an award given in this relationship.
- 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_69a88643a3388190a612f2ebe1fb29e7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab694d75ac8190a4d61399c04b9fb9 |
completed | March 6, 2026, 11:54 p.m. |
| PD | Predicate disambiguation | batch_69aa61d6b8ec8190a1597b2e44ea6534 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:32 p.m.