Triple

T18491386
Position Surface form Disambiguated ID Type / Status
Subject Academy of Medical Royal Colleges E451824 entity
Predicate shortName P43 FINISHED
Object AoMRC 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: AoMRC | Statement: [Academy of Medical Royal Colleges, shortName, AoMRC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AoMRC
Context triple: [Academy of Medical Royal Colleges, shortName, AoMRC]
  • A. MRC
    MRC is a research and education center at the University of Maryland focused on advancing robotics and autonomous systems.
  • B. MRC
    MRC is an American independent film and television studio known for producing and financing a wide range of acclaimed movies and TV series.
  • C. MRC
    MRC is an intergovernmental organization that coordinates sustainable development and management of the Mekong River basin among its member countries.
  • D. MRC chosen
    MRC is a major UK organization that funds and supports medical research to improve human health.
  • E. AMRO
    AMRO is the World Health Organization’s Regional Office responsible for public health leadership and coordination across the Americas.
  • 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_69d8d3855d50819097fc8561b0299dd9 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e531dcac3c8190b2ebd129ca7f368d completed April 19, 2026, 7:49 p.m.
Created at: April 10, 2026, 11:35 a.m.