Triple

T2589521
Position Surface form Disambiguated ID Type / Status
Subject MedStar Georgetown University Hospital E58084 entity
Predicate hasTeachingStatus P40561 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: [MedStar Georgetown University Hospital, hasTeachingStatus, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasTeachingStatus
Context triple: [MedStar Georgetown University Hospital, hasTeachingStatus, yes]
  • A. hasTeachingRole
    Indicates that one entity holds a position or responsibility involving teaching or instruction in relation to another entity.
  • B. hasTeaching
    Indicates that one entity provides instruction or educational guidance to another entity.
  • C. hasTeachingAuthority
    Indicates that one entity possesses the recognized power or right to teach, instruct, or provide formal education to another entity or within a specific context.
  • D. hasTeachingActivity
    Indicates that an entity engages in or is associated with a specific teaching-related activity or instructional role.
  • E. hasEducationalRole
    Indicates that an entity holds a specific function, position, or responsibility within an educational context or setting.
  • 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_69ab4ac019c8819094add11c46706e32 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd3feb45c81909369a49c3990294a completed March 7, 2026, 7:30 a.m.
PD Predicate disambiguation batch_69abd0d19308819089ee942513d567a4 completed March 7, 2026, 7:16 a.m.
PDg Predicate description generation batch_69abd37ef248819090ab6b86b67e355f completed March 7, 2026, 7:27 a.m.
Created at: March 6, 2026, 9:49 p.m.