Triple

T885030
Position Surface form Disambiguated ID Type / Status
Subject Croatia E19110 entity
Predicate largestCity P235 FINISHED
Object Zagreb E31635 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: Zagreb | Statement: [Croatia, largestCity, Zagreb]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zagreb
Context triple: [Croatia, largestCity, 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. 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.
  • C. 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.
  • D. Ljubljana
    Ljubljana is the capital and largest city of Slovenia, known for its picturesque old town, Baroque and Art Nouveau architecture, and vibrant cultural scene along the Ljubljanica River.
  • E. 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.
  • 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_69a4939c32488190a7ccd41cf0abb22b completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ace5e15c81908cc2e648c9cd52f2 completed March 1, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac5e990be881908b47d88074339470 completed March 7, 2026, 5:21 p.m.
Created at: March 1, 2026, 7:39 p.m.