Triple

T6233241
Position Surface form Disambiguated ID Type / Status
Subject Advocate Lutheran General Hospital E139406 entity
Predicate hasMedicalEducationProgram P2489 FINISHED
Object residency programs 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: residency programs | Statement: [Advocate Lutheran General Hospital, hasMedicalEducationProgram, residency programs]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasMedicalEducationProgram
Context triple: [Advocate Lutheran General Hospital, hasMedicalEducationProgram, residency programs]
  • A. hasMedicalCollege
    Indicates that one entity possesses, hosts, or includes a medical college as part of its organization or structure.
  • B. hasEducationalProgram chosen
    Indicates that an entity offers, runs, or is associated with a specific educational program.
  • C. hasPharmacySchool
    Indicates that an institution or entity includes, operates, or is affiliated with a school or program dedicated to the study and training of pharmacy.
  • D. medicalSchool
    Indicates that one entity serves as the medical school where the other entity received medical education or training.
  • E. coordinatesMedicalEducation
    Indicates that one entity organizes, manages, or oversees the medical education activities or programs involving 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_69c008b0e7ac8190808a59573ee646f3 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062efa25c8190a54f5a6f5b5ad24f completed March 22, 2026, 9:45 p.m.
PD Predicate disambiguation batch_69c05601de6481909d0880048fd7b49a completed March 22, 2026, 8:50 p.m.
Created at: March 22, 2026, 4:22 p.m.