Triple
T2347023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Title XVIII of the Social Security Act |
E45153
|
entity |
| Predicate | hasBeneficiaryGroup |
P22506
|
FINISHED |
| Object | Medicare beneficiaries |
—
|
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: Medicare beneficiaries | Statement: [Title XVIII of the Social Security Act, hasBeneficiaryGroup, Medicare beneficiaries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBeneficiaryGroup Context triple: [Title XVIII of the Social Security Act, hasBeneficiaryGroup, Medicare beneficiaries]
-
A.
hasSupporterGroup
Indicates that an entity is associated with a group of supporters that backs, promotes, or advocates for it.
-
B.
hasUserGroup
Indicates that a user is associated with, belongs to, or is a member of a specific user group.
-
C.
hasRelatedGroup
Indicates that one group or collection is associated with another group or collection through some defined relationship or connection.
-
D.
beneficiaryType
chosen
Indicates the type or category of beneficiary that receives or is intended to receive the benefit or outcome of an action or resource.
-
E.
hasPatientGroup
Indicates a relationship in which an entity (such as a study, treatment, or clinical activity) is associated with a specific group of patients it involves or targets.
- 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_69a88917935081909b755dbf38e81024 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abcade3c808190ab3803538ccbe620 |
completed | March 7, 2026, 6:51 a.m. |
| PD | Predicate disambiguation | batch_69abc59616a8819099711834e6f1ccd6 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:52 p.m.