Triple

T6793719
Position Surface form Disambiguated ID Type / Status
Subject Tuzla E155997 entity
Predicate hasTwinTown P919 FINISHED
Object Osijek E133925 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: Osijek | Statement: [Tuzla, hasTwinTown, Osijek]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Osijek
Context triple: [Tuzla, hasTwinTown, Osijek]
  • A. Osijek chosen
    Osijek is a prominent city in eastern Croatia known as an economic, cultural, and educational center of the Slavonia region.
  • B. Karlovac
    Karlovac is a historic Croatian city strategically located at the confluence of four rivers, known for its star-shaped Renaissance fortress and role as a key military and trading center.
  • C. Zagreb
    Zagreb is the capital and largest city of Croatia, known as a political, cultural, and economic hub in the Balkans.
  • D. Slavonski Brod
    Slavonski Brod is a major city in eastern Croatia situated on the border with Bosnia and Herzegovina, known as an important industrial and transport hub on the Sava River.
  • E. Barajevo
    Barajevo is a suburban municipality of Belgrade, Serbia, located in the southern part of the city’s administrative area.
  • 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_69c6881844448190a65822d9b39d7f88 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d2af6f908190809e39b73894e513 completed March 27, 2026, 6:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c74253f9b4819099057c730237c269 completed March 28, 2026, 2:52 a.m.
Created at: March 27, 2026, 2:15 p.m.