Triple
T29550114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. Small Business Administration loan programs |
E749743
|
entity |
| Predicate | typicalLoanSizeRange |
P13474
|
FINISHED |
| Object | microloans up to around $50,000 |
—
|
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: microloans up to around $50,000 | Statement: [U.S. Small Business Administration loan programs, typicalLoanSizeRange, microloans up to around $50,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalLoanSizeRange Context triple: [U.S. Small Business Administration loan programs, typicalLoanSizeRange, microloans up to around $50,000]
-
A.
typicalInvestmentSize
Indicates the usual or most common amount of money invested in a single investment or deal.
-
B.
typicalRange
chosen
Indicates the usual or expected range of values, conditions, or states within which something normally occurs or applies.
-
C.
loanLimitType
Indicates the category or rule that defines how a loan’s maximum allowable amount or terms are limited.
-
D.
maximumLoanAmountUSD
Indicates the highest amount of money, expressed in U.S. dollars, that can be loaned under a given agreement or condition.
-
E.
typicalLoanPurpose
Indicates the usual or intended purpose for which a loan is taken or used.
- 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_69f0bd48691081908cecad39bac591e0 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_6a01d7b3ce8c8190b2f90be730505765 |
completed | May 11, 2026, 1:20 p.m. |
| PD | Predicate disambiguation | batch_6a01d5115a6c8190a6d9f96ec484135a |
completed | May 11, 2026, 1:09 p.m. |
Created at: April 28, 2026, 5:11 p.m.