Triple

T632010
Position Surface form Disambiguated ID Type / Status
Subject Islamic world E15944 entity
Predicate hasCulturalCenter P2412 FINISHED
Object Sarajevo E21865 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: Sarajevo | Statement: [Islamic world, hasCulturalCenter, Sarajevo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sarajevo
Context triple: [Islamic world, hasCulturalCenter, Sarajevo]
  • A. Sarajevo chosen
    Sarajevo is the capital and largest city of Bosnia and Herzegovina, historically known as the site of Archduke Franz Ferdinand’s assassination that sparked World War I.
  • B. Belgrade
    Belgrade is the capital and largest city of Serbia, historically significant as a strategic crossroads between Central Europe and the Balkans on the confluence of the Sava and Danube rivers.
  • C. Zagreb
    Zagreb is the capital and largest city of Croatia, known as a political, cultural, and economic hub in the Balkans.
  • D. Novi Sad
    Novi Sad is Serbia’s second-largest city and the cultural and economic center of the northern Vojvodina region, known for its historic architecture and the EXIT music festival.
  • E. Podgorica
    Podgorica is the capital and largest city of Montenegro, serving as its political, economic, and cultural center in the Balkans.
  • 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_69a4935c131c8190a5378c6bf101e8cc completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49ec2a4c08190bc5c6ce8a10b0967 completed March 1, 2026, 8:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69a63742d8a8819087c7c2fa2430da75 completed March 3, 2026, 1:20 a.m.
Created at: March 1, 2026, 7:35 p.m.