Triple

T3769503
Position Surface form Disambiguated ID Type / Status
Subject ERM E82761 entity
Predicate followedBy P78 FINISHED
Object ERM II E82761 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: ERM II | Statement: [ERM, followedBy, ERM II]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ERM II
Context triple: [ERM, followedBy, ERM II]
  • A. 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.
  • B. ERM chosen
    ERM is a European Union system designed to reduce exchange rate variability and achieve monetary stability in preparation for economic and monetary union.
  • C. SOM II
    SOM II is the second session in a series of high-level Senior Officials' Meetings where government representatives coordinate and prepare policy and agenda items for ministerial or leaders’ summits.
  • D. SII
    SII is the abbreviated name for the Military and Information Security Service, a national agency responsible for safeguarding defense-related and sensitive information.
  • E. EMRO
    EMRO is the World Health Organization’s regional office responsible for public health coordination and support across the Eastern Mediterranean region.
  • 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_69ad8b207b0081909d2b48843fbd8795 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcc2f016c81909c2e3c85dbc3c259 completed March 8, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4e5287908819084319b8dfa407635 completed March 14, 2026, 4:33 a.m.
Created at: March 8, 2026, 3:35 p.m.