Triple

T1140943
Position Surface form Disambiguated ID Type / Status
Subject Medicare Part B E23447 entity
Predicate enrollmentType P26488 FINISHED
Object voluntary enrollment 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: voluntary enrollment | Statement: [Medicare Part B, enrollmentType, voluntary enrollment]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: enrollmentType
Context triple: [Medicare Part B, enrollmentType, voluntary enrollment]
  • A. enrollmentModel
    Indicates the type or structure of the enrollment relationship that governs how entities (such as users or participants) are registered or associated with a program, course, or service.
  • B. hasStudentEnrollment
    Indicates that a person or entity is enrolled as a student in a particular course, program, or educational institution.
  • C. admissionType
    Indicates the category or manner in which an entity (such as a person or case) is formally accepted or admitted into a system, institution, or process.
  • D. enrolledForm
    Indicates that an entity is formally registered or signed up to participate in a particular form, program, or course.
  • E. educationType
    Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
  • 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_69a493ef399c8190b04b9146d2314f59 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4bde18d208190848c189b2b8d585f completed March 1, 2026, 10:29 p.m.
PD Predicate disambiguation batch_69a4bb4b52d48190bec2e7ad1cc8efc0 completed March 1, 2026, 10:18 p.m.
PDg Predicate description generation batch_69a4bddfa598819088690e1ab010ba0b completed March 1, 2026, 10:29 p.m.
Created at: March 1, 2026, 7:44 p.m.