Triple

T37099012
Position Surface form Disambiguated ID Type / Status
Subject Maimonides Medical Center E918643 entity
Predicate hasPediatricsDepartment P197375 FINISHED
Object yes 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: yes | Statement: [Maimonides Medical Center, hasPediatricsDepartment, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasPediatricsDepartment
Context triple: [Maimonides Medical Center, hasPediatricsDepartment, yes]
  • A. hasPediatricHospital
    Indicates that an entity possesses or is associated with a hospital facility that provides medical services specifically for children.
  • B. hasPharmacyDepartment
    Indicates that an entity includes or is associated with a dedicated pharmacy department or unit.
  • C. designatedAsFlagshipHospitalFor
    Indicates that one hospital has been officially selected or recognized as the primary or leading flagship institution for another entity (such as a health system, region, or organization).
  • D. isPublicHospital
    Indicates that a hospital is owned, funded, or operated by a government or public authority rather than by private entities.
  • E. hasAnesthesiologyDepartment
    Indicates that an entity includes or is associated with a department specializing in anesthesiology services.
  • 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_69f76e9a48bc8190a3947508d8bca408 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fe8ddf70e48190a917eb9e8f7b6966 completed May 9, 2026, 1:29 a.m.
PD Predicate disambiguation batch_69fe87ef94dc81909bb00ec8d6de9bcd completed May 9, 2026, 1:03 a.m.
PDg Predicate description generation batch_69fe8dde8d008190b03dc0f97618073c completed May 9, 2026, 1:29 a.m.
Created at: May 3, 2026, 4:14 p.m.