Triple
T6778081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Production Credit Association |
E155608
|
entity |
| Predicate | lendingHorizon |
P10122
|
FINISHED |
| Object | short-term loans |
—
|
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: short-term loans | Statement: [Production Credit Association, lendingHorizon, short-term loans]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lendingHorizon Context triple: [Production Credit Association, lendingHorizon, short-term loans]
-
A.
timeHorizonOfLoans
chosen
Indicates the length of time over which loans are scheduled to be outstanding or repaid.
-
B.
lender
Indicates a relationship where one party provides something, typically money or resources, to another with the expectation of repayment or return.
-
C.
lendingArm
Indicates that one entity provides financial support or resources to another, typically in the form of a loan or credit.
-
D.
lenderType
Indicates the classification or category of the lender involved in a lending relationship (e.g., bank, individual, institution).
-
E.
loanSource
Indicates that one entity is the origin or provider of a loan extended to another entity.
- 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_69c688162bf8819088b664b5c3b5be7a |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2689d408190bc2c1ce4ae9c1b13 |
completed | March 27, 2026, 6:54 p.m. |
| PD | Predicate disambiguation | batch_69c6d095dcac8190bb9b943f50a7f885 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:13 p.m.