Triple

T21484521
Position Surface form Disambiguated ID Type / Status
Subject International Bank for Economic Cooperation E530082 entity
Predicate regionServed P82 FINISHED
Object Eurasia 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: Eurasia | Statement: [International Bank for Economic Cooperation, regionServed, Eurasia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eurasia
Context triple: [International Bank for Economic Cooperation, regionServed, Eurasia]
  • A. Eurasia chosen
    Eurasia is the vast combined continental landmass of Europe and Asia, forming the largest continuous land area on Earth.
  • B. Asya
    Asya is a common Russian diminutive form of the female given name Anastasia.
  • C. Euravia
    Euravia was the original name of the British charter airline that later became known as Britannia Airways.
  • D. Asia–Europe
    Asia–Europe is a major intercontinental shipping and trade route connecting key ports across the Asian and European continents.
  • E. Afro-Eurasia
    Afro-Eurasia is the vast continuous landmass comprising the continents of Africa, Europe, and Asia, forming the largest connected continental area on Earth.
  • 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_69e0c45acc3881908e38d3f28964152b completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9ea365a8481909635f614b23e751f completed April 23, 2026, 9:45 a.m.
Created at: April 16, 2026, 6:21 p.m.