Triple
T6778029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Intermediate Credit Banks |
E155607
|
entity |
| Predicate | servedBorrowers |
P69284
|
FINISHED |
| Object | farmers |
—
|
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: farmers | Statement: [Federal Intermediate Credit Banks, servedBorrowers, farmers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedBorrowers Context triple: [Federal Intermediate Credit Banks, servedBorrowers, farmers]
-
A.
hasBorrowingsFrom
Indicates that one entity has taken, adopted, or derived elements (such as features, ideas, or content) from another entity.
-
B.
loanedTo
Indicates that one entity has temporarily provided something it owns or controls to another entity with the expectation of its return.
-
C.
borrower
Indicates a relationship where one entity temporarily receives and uses something belonging to another entity, typically with the obligation to return it.
-
D.
targetBorrowers
chosen
Indicates that certain entities are the intended or eligible recipients of a loan or borrowing arrangement from another entity.
-
E.
servedPerson
Indicates that one entity has provided service, assistance, or attention 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.