Triple
T37310563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Missouri ABLE savings program |
E926194
|
entity |
| Predicate | protectsBenefit |
P74494
|
FINISHED |
| Object | Supplemental Security Income |
—
|
NE NERFINISHED |
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: Supplemental Security Income | Statement: [Missouri ABLE savings program, protectsBenefit, Supplemental Security Income]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protectsBenefit Context triple: [Missouri ABLE savings program, protectsBenefit, Supplemental Security Income]
-
A.
benefitProtection
chosen
Indicates that one entity provides protective advantages or safeguards that benefit another entity.
-
B.
protects
Indicates taking action to keep someone or something safe from harm, danger, or negative effects.
-
C.
benefitAppliesTo
Indicates that a particular benefit is applicable to, or valid for, a specified entity or context.
-
D.
safetyBenefit
Indicates that one entity provides, contributes to, or results in an improvement in the safety or risk reduction experienced by another entity.
-
E.
beneficiaryCoverage
Indicates that one entity provides or is responsible for insurance or financial coverage benefits received by 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_69f76eb1bc508190924e9fa5d8acdeb3 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb78cbef988190b8f79d946b46e6b2 |
completed | May 6, 2026, 5:22 p.m. |
| PD | Predicate disambiguation | batch_69fb5a9ac5a08190b24ef308963fc52b |
completed | May 6, 2026, 3:13 p.m. |
Created at: May 3, 2026, 4:16 p.m.