Triple
T7569955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marginal standing facility rate |
E179213
|
entity |
| Predicate | borrowerType |
P69284
|
FINISHED |
| Object | Commercial banks |
—
|
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: Commercial banks | Statement: [Marginal standing facility rate, borrowerType, Commercial banks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borrowerType Context triple: [Marginal standing facility rate, borrowerType, Commercial banks]
-
A.
lenderType
Indicates the classification or category of the lender involved in a lending relationship (e.g., bank, individual, institution).
-
B.
borrower
Indicates a relationship where one entity temporarily receives and uses something belonging to another entity, typically with the obligation to return it.
-
C.
targetBorrowers
chosen
Indicates that certain entities are the intended or eligible recipients of a loan or borrowing arrangement from another entity.
-
D.
beneficiaryType
Indicates the type or category of beneficiary that receives or is intended to receive the benefit or outcome of an action or resource.
-
E.
eligibleBorrower
Indicates that an entity meets the required conditions to be allowed to borrow (e.g., money, items, or resources) under a given set of rules or policies.
- 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_69c69f316e50819081a271c85c06f918 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f91ec780819099de6227a27bf5a5 |
completed | March 27, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69c6f4de77048190b8769e717fdcf8e7 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:51 p.m.