Triple
T24734233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Farm Credit Banks |
E618367
|
entity |
| Predicate | distributesFundsTo |
P66766
|
FINISHED |
| Object | local Farm Credit associations |
—
|
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: local Farm Credit associations | Statement: [Farm Credit Banks, distributesFundsTo, local Farm Credit associations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distributesFundsTo Context triple: [Farm Credit Banks, distributesFundsTo, local Farm Credit associations]
-
A.
disburses
chosen
Indicates the act of paying out or distributing funds or resources from a source to a recipient.
-
B.
operatesFund
Indicates that an entity manages and runs the activities or investments of a particular fund.
-
C.
funds
Indicates that one entity provides financial resources or monetary support to another entity or activity.
-
D.
usedFund
Indicates that one entity expended or applied a particular fund or financial resource for some purpose.
-
E.
redistributes
Indicates the action of taking resources, benefits, or responsibilities from one or more entities and allocating or spreading them among others, often to achieve a different or more balanced distribution.
- 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_69e2fab772608190b74163751047ff50 |
completed | April 18, 2026, 3:29 a.m. |
| NER | Named-entity recognition | batch_69f47b865df48190bf4b6d3e9f9305e6 |
completed | May 1, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_69f4682c8a3c8190adbfaac99474eaaf |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 18, 2026, 4:03 a.m.