Triple
T414390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Social Security system |
E9559
|
entity |
| Predicate | benefitFormulaBasis |
P6447
|
FINISHED |
| Object | earnings history |
—
|
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: earnings history | Statement: [United States Social Security system, benefitFormulaBasis, earnings history]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: benefitFormulaBasis Context triple: [United States Social Security system, benefitFormulaBasis, earnings history]
-
A.
benefitForm
Indicates that one entity is a specific form, type, or variant in which a benefit is provided or realized for another entity.
-
B.
calculationBasis
chosen
Indicates the rule, method, or reference standard used as the foundation for performing a calculation in the relationship.
-
C.
hasBenefit
Indicates that one entity provides an advantage, improvement, or positive outcome to another entity.
-
D.
benefits
Indicates that one entity gains an advantage, improvement, or positive outcome as a result of another entity or action.
-
E.
beneficiaries
Indicates that certain entities receive advantages, profits, or positive outcomes from an action, event, or arrangement.
- 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.