Triple

T3525929
Position Surface form Disambiguated ID Type / Status
Subject Drava E74537 entity
Predicate flowsThroughCity P10456 FINISHED
Object Varaždin E188012 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: Varaždin | Statement: [Drava, flowsThroughCity, Varaždin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Varaždin
Context triple: [Drava, flowsThroughCity, Varaždin]
  • A. Varaždin, Croatia chosen
    Varaždin is a historic city in northern Croatia known for its well-preserved baroque architecture, former status as the country’s capital, and vibrant cultural festivals.
  • B. Prijedor
    Prijedor is a city in northwestern Bosnia and Herzegovina known for its industrial heritage and its significant role and tragic events during the Bosnian War.
  • C. Zrenjanin
    Zrenjanin is a city in northern Serbia known as an economic, cultural, and administrative center of the Banat region.
  • D. Lazarevac
    Lazarevac is a suburban municipality of Belgrade in central Serbia, known for its coal mining industry and the Kolubara coal basin.
  • 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_69ad85d0c5488190a3d8e02ebd01a1aa completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc6a8d0c819094d38b9c47fb67b4 completed March 8, 2026, 6:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37e8de2648190809369c3f0b7d85d completed March 13, 2026, 3:03 a.m.
Created at: March 8, 2026, 3:19 p.m.