Triple
T1095085
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Medicare Part D |
E24252
|
entity |
| Predicate | hasLowIncomeSubsidyProgram |
P23815
|
FINISHED |
| Object | Extra Help |
—
|
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: Extra Help | Statement: [Medicare Part D, hasLowIncomeSubsidyProgram, Extra Help]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLowIncomeSubsidyProgram Context triple: [Medicare Part D, hasLowIncomeSubsidyProgram, Extra Help]
-
A.
eligibilityAfterExpansion
Indicates that an entity becomes eligible for a benefit, status, or condition only after a specified expansion, change, or extension has taken place.
-
B.
hasPublicHousing
Indicates that a location or jurisdiction provides or contains government-funded residential housing available to the public.
-
C.
hasLow
Indicates that an entity possesses a value, level, or amount of something that is below a defined or expected threshold.
-
D.
hasBenefit
Indicates that one entity provides an advantage, improvement, or positive outcome to another entity.
-
E.
federalSchemeImplemented
Indicates that a specific federal government program or policy has been put into operation or carried out in practice.
- F. None of above. chosen
Provenance (4 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_69a4940542308190ac2a0b1f730b7cfc |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b99e92308190b8a8c499e1630672 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b743175481908f3967e589717c55 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b80f0fb08190a19a50e38ae8f16c |
completed | March 1, 2026, 10:05 p.m. |
Created at: March 1, 2026, 7:42 p.m.