Triple

T19756313
Position Surface form Disambiguated ID Type / Status
Subject Ben Taub Hospital E474509 entity
Predicate name P16 FINISHED
Object Ben Taub Hospital NE NERFINISHED

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: Ben Taub Hospital | Statement: [Ben Taub Hospital, name, Ben Taub Hospital]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ben Taub Hospital
Context triple: [Ben Taub Hospital, name, Ben Taub Hospital]
  • A. Ben Taub Hospital chosen
    Ben Taub Hospital is a major public teaching and trauma hospital in Houston, Texas, known for providing comprehensive emergency and specialty care as part of the Texas Medical Center.
  • B. Maimonides Medical Center
    Maimonides Medical Center is a major nonprofit teaching hospital and healthcare provider based in Brooklyn, New York.
  • C. Herzog Hospital
    Herzog Hospital is a major medical center in Jerusalem, Israel, known especially for geriatric, psychiatric, and long-term care services.
  • D. Carmel Medical Center
    Carmel Medical Center is a major hospital in Haifa, Israel, providing a wide range of medical and surgical services as part of the Clalit Health Services network.
  • E. Mount Sinai Hospital
    Mount Sinai Hospital is a major academic and teaching hospital in downtown Toronto, renowned for its specialized care, research, and affiliation with the University of Toronto.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51940a0819087bd2996f98da668 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6531afcbc8190bd5364700008f6d8 completed April 20, 2026, 4:23 p.m.
Created at: April 10, 2026, 1:48 p.m.