Triple

T10953212
Position Surface form Disambiguated ID Type / Status
Subject UofK E258774 entity
Predicate hasCampus P116 FINISHED
Object Medical Campus E258761 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: Medical Campus | Statement: [UofK, hasCampus, Medical Campus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Medical Campus
Context triple: [UofK, hasCampus, Medical Campus]
  • A. Medical Campus chosen
    Medical Campus is the dedicated health sciences and clinical training campus of the University of Khartoum in Sudan.
  • B. Medical Campus
    The Medical Campus is Boston University's dedicated hub for health sciences education, research, and clinical care.
  • C. Medical Campus
    Medical Campus is a specialized university or institutional area dedicated to medical education, research, and healthcare facilities.
  • D. Medical Sciences Campus
    The Medical Sciences Campus is a specialized branch of Université Saint-Joseph de Beyrouth dedicated to education and research in medicine and health-related disciplines.
  • E. Medical School Campus
    The Medical School Campus is the dedicated health sciences and clinical training hub of the University of the Witwatersrand in Johannesburg, South Africa.
  • 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_69d6aa88500c819097d7032ca578e74f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770fe4cfc81909032296c31e077f0 completed April 9, 2026, 9:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2d733f7d88190b45df5c155ff5a46 completed April 18, 2026, 12:58 a.m.
Created at: April 8, 2026, 9:23 p.m.