Triple

T3894709
Position Surface form Disambiguated ID Type / Status
Subject armed forces of the Habsburg Monarchy E88140 entity
Predicate garrisonedIn P2911 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: [armed forces of the Habsburg Monarchy, garrisonedIn, Zagreb]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zagreb
Context triple: [armed forces of the Habsburg Monarchy, garrisonedIn, 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. 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.
  • D. 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.
  • 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_69aed9466d548190939f5217a23ed4ac completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeecd06cbc8190938d9f91388ad290 completed March 9, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69b51c99bab88190bd63f5b9b3950001 completed March 14, 2026, 8:30 a.m.
Created at: March 9, 2026, 3:21 p.m.