Triple

T469936
Position Surface form Disambiguated ID Type / Status
Subject Francis Nurse E8532 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: [Francis Nurse, familyName, Nurse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nurse
Context triple: [Francis 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. 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.
  • C. Richard Nurse
    Richard Nurse is a Canadian former professional ice hockey player who competed in the World Hockey Association during the 1970s.
  • D. 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.
  • E. School of Nursing
    The School of Nursing at Georgetown University is an academic division dedicated to educating nurses and advancing nursing research and practice within a Jesuit, values-based framework.
  • 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_69a2e7f3aeb48190a19453e3a043f486 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2efef8b788190857ebf66df562d59 completed Feb. 28, 2026, 1:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69a45803a8c081908e5f5a03f462cd2e completed March 1, 2026, 3:15 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.