Triple
T1150084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Medicare Part C |
E23655
|
entity |
| Predicate | includesPlanType |
P5640
|
FINISHED |
| Object | Health Maintenance Organization plan |
—
|
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: Health Maintenance Organization plan | Statement: [Medicare Part C, includesPlanType, Health Maintenance Organization plan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesPlanType Context triple: [Medicare Part C, includesPlanType, Health Maintenance Organization plan]
-
A.
offersPlanType
chosen
Indicates that one entity provides or makes available a specific type of plan to another entity or in a given context.
-
B.
planType
Indicates the specific category or kind of plan associated with an entity, such as its level, structure, or intended use.
-
C.
hasPlan
Indicates that an entity possesses or is associated with a specific plan or course of action.
-
D.
containsRideType
Indicates that one entity includes or offers a specific type or category of ride as part of its available options.
-
E.
insuranceType
Indicates the specific category or kind of insurance coverage associated with an entity or relationship.
- 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_69a493f0d32c8190ac74bad3c87f2641 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bd0bed00819091d71983d787a030 |
completed | March 1, 2026, 10:26 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4ee3988190ac89c5ae5b10e316 |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:44 p.m.