Triple

T1646330
Position Surface form Disambiguated ID Type / Status
Subject Nick Nurse E35590 entity
Predicate familyName P18 FINISHED
Object Nurse E3911 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: Nurse | Statement: [Nick Nurse, familyName, Nurse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nurse
Context triple: [Nick Nurse, familyName, Nurse]
  • A. Nurse chosen
    Nurse is a common English occupational surname originally referring to someone who worked as a caregiver or medical attendant.
  • B. Nurses
    Nurses is an American sitcom that follows the personal and professional lives of a group of nurses working at a Miami hospital.
  • C. RN
    RN is the commonly used abbreviation for "RN: The Memoirs of Richard Nixon," the former U.S. president’s autobiographical account of his life and political career.
  • D. Richard Nurse
    Richard Nurse is a Canadian former professional ice hockey player who competed in the World Hockey Association during the 1970s.
  • E. School of Nursing
    The School of Nursing at George Washington University is an academic division dedicated to educating nurses and advancing nursing research and practice within the university’s health sciences programs.
  • 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_69a88604618c81908b41f6429c431eb6 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90a62b26c8190bf97bb80c228b47e completed March 5, 2026, 4:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad60a4bd5481908b46f44364c15592 completed March 8, 2026, 11:42 a.m.
Created at: March 4, 2026, 7:28 p.m.