Triple

T9579149
Position Surface form Disambiguated ID Type / Status
Subject Dr. Christopher Turk E231123 entity
Predicate employer P7 FINISHED
Object Sacred Heart Hospital E809311 NE 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: Sacred Heart Hospital | Statement: [Dr. Christopher Turk, employer, Sacred Heart Hospital]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sacred Heart Hospital
Context triple: [Dr. Christopher Turk, employer, Sacred Heart Hospital]
  • A. Sacred Heart Hospital chosen
    Sacred Heart Hospital is the fictional teaching hospital where most of the events and character interactions in the medical comedy series "Scrubs" take place.
  • B. Holy Family Hospital
    Holy Family Hospital is a major public teaching and referral hospital located in Rawalpindi, Pakistan.
  • C. Catholic Medical Center
    Catholic Medical Center is a major acute-care hospital and healthcare provider serving the Manchester, New Hampshire region.
  • D. Lutheran Medical Center
    Lutheran Medical Center is a major community hospital and healthcare facility serving Wheat Ridge and the greater Denver metropolitan area in Colorado.
  • E. Holy Name Medical Center
    Holy Name Medical Center is a nonprofit community hospital and healthcare facility located in Teaneck, New Jersey.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69ca848091c48190bc313d6620d09555 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd99aece1081908287e03106de020f completed April 1, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1790fbfb88190b1d12f5ed3d4ef7e completed April 4, 2026, 8:48 p.m.
Created at: March 30, 2026, 8:05 p.m.