Triple
T24734273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Farm Credit System |
E618368
|
entity |
| Predicate | hasGuarantee |
P52798
|
FINISHED |
| Object | not federally guaranteed |
—
|
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: not federally guaranteed | Statement: [Federal Farm Credit System, hasGuarantee, not federally guaranteed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGuarantee Context triple: [Federal Farm Credit System, hasGuarantee, not federally guaranteed]
-
A.
typeOfGuarantees
Indicates the specific kind or category of guarantees that one entity provides, holds, or is associated with in relation to another.
-
B.
guaranteeStatus
chosen
Indicates the current state or condition of a guarantee associated with an entity or agreement.
-
C.
mayGuarantee
Indicates that one entity has the potential or authority to provide a guarantee for another entity or outcome.
-
D.
guaranteeCoverage
Indicates that one party commits to providing financial or protective coverage for another party or specified situation.
-
E.
seeksGuaranteesFor
Indicates that one entity actively pursues or requests assurances, protections, or commitments from another entity regarding a specific matter or outcome.
- 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_69f422aee0408190899efe7e24ef2b40 |
completed | May 1, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69f420e92cc88190a803aecdae78a051 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 4:03 a.m.