Triple
T414384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Social Security system |
E9559
|
entity |
| Predicate | financingMechanism |
P59
|
FINISHED |
| Object | pay-as-you-go |
—
|
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: pay-as-you-go | Statement: [United States Social Security system, financingMechanism, pay-as-you-go]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: financingMechanism Context triple: [United States Social Security system, financingMechanism, pay-as-you-go]
-
A.
fundingModel
chosen
Indicates how an entity is financially supported or sustained, such as through specific revenue sources, payment structures, or funding mechanisms.
-
B.
loanType
Indicates the specific category or kind of loan associated with an entity or transaction.
-
C.
funds
Indicates that one entity provides financial resources or monetary support to another entity or activity.
-
D.
definesMechanism
Indicates that one entity specifies or explains the underlying process or mechanism by which another entity operates or occurs.
-
E.
monetaryComponent
Indicates that something is a financial element or part of a larger monetary value, structure, or transaction.
- 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_69a2e80111fc8190961d5b7c6154123f |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2eebde1d881908fb212bfba9d7c67 |
completed | Feb. 28, 2026, 1:33 p.m. |
| PD | Predicate disambiguation | batch_69a2edcff4688190809d83d112ff25a5 |
completed | Feb. 28, 2026, 1:29 p.m. |
Created at: Feb. 28, 2026, 1:09 p.m.