Triple

T2158326
Position Surface form Disambiguated ID Type / Status
Subject EMRO E47943 entity
Predicate acronym P43 FINISHED
Object EMRO E47943 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: EMRO | Statement: [EMRO, acronym, EMRO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: EMRO
Context triple: [EMRO, acronym, EMRO]
  • A. EMRO chosen
    EMRO is the World Health Organization’s regional office responsible for public health coordination and support across the Eastern Mediterranean region.
  • B. ERM
    ERM is the French-language abbreviation for Belgium’s Royal Military Academy, the country’s principal institution for training future officers of the armed forces.
  • C. ERM
    ERM is a European Union system designed to reduce exchange rate variability and achieve monetary stability in preparation for economic and monetary union.
  • D. EMD
    EMD is the commonly used abbreviation for the Engineering Management Division, a professional group focused on the practice and advancement of engineering management.
  • E. EMD
    EMD is the vehicle registration code assigned to the German town of Emden.
  • 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_69a88a1d1fd8819088b34990d69a712f completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abbe68fe0c8190beb5db003738a6e5 completed March 7, 2026, 5:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae58e796e88190a8d86979c7ff952f completed March 9, 2026, 5:21 a.m.
Created at: March 4, 2026, 7:44 p.m.