Triple

T19311708
Position Surface form Disambiguated ID Type / Status
Subject Ivica Račan E482986 entity
Predicate workLocation P7 FINISHED
Object Zagreb 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: Zagreb | Statement: [Ivica Račan, workLocation, Zagreb]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zagreb
Context triple: [Ivica Račan, workLocation, Zagreb]
  • A. Zagreb chosen
    Zagreb is the capital and largest city of Croatia, known as a political, cultural, and economic hub in the Balkans.
  • B. Osijek
    Osijek is a prominent city in eastern Croatia known as an economic, cultural, and educational center of the Slavonia region.
  • C. 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.
  • D. 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.
  • E. Rijeka
    Rijeka is a significant Croatian port city on the Adriatic Sea, known for its maritime industry, cultural heritage, and role as a key transport hub.
  • 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_69d8e8d04d5c8190baa816986f2b1d1e completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e604ce5de081909811c49f56ba94bb completed April 20, 2026, 10:49 a.m.
Created at: April 10, 2026, 1:32 p.m.