Triple

T15557972
Position Surface form Disambiguated ID Type / Status
Subject Vrbas E370919 entity
Predicate flowsThrough P225 FINISHED
Object Banja Luka E154645 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: Banja Luka | Statement: [Vrbas, flowsThrough, Banja Luka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Banja Luka
Context triple: [Vrbas, flowsThrough, Banja Luka]
  • A. Banja Luka chosen
    Banja Luka is the second-largest city of Bosnia and Herzegovina and the administrative center of the Republika Srpska entity, known for its riverside setting, Austro-Hungarian architecture, and cultural life.
  • B. Bajina Bašta
    Bajina Bašta is a small town in western Serbia known for its scenic location on the Drina River and proximity to the Tara National Park.
  • C. Goražde
    Goražde is a town in eastern Bosnia and Herzegovina that became internationally known for its siege and designation as a UN-protected enclave during the Bosnian War.
  • D. Zrenjanin
    Zrenjanin is a city in northern Serbia known as an economic, cultural, and administrative center of the Banat region.
  • E. Sarajevo
    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.
  • 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_69d85cc6cf40819091f4a5facee1ebe6 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04dda3ab88190ab383333ce69fe8f completed April 16, 2026, 2:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff82e56ffc81909e3228a660df4e09 completed May 9, 2026, 6:54 p.m.
Created at: April 10, 2026, 4:09 a.m.