Triple

T4323033
Position Surface form Disambiguated ID Type / Status
Subject Lika-Senj County E96563 entity
Predicate containsSettlement P847 FINISHED
Object Gospić E108548 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: Gospić | Statement: [Lika-Senj County, containsSettlement, Gospić]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gospić
Context triple: [Lika-Senj County, containsSettlement, Gospić]
  • A. Gospić chosen
    Gospić is a town in the Lika region of Croatia, known as the administrative center of Lika-Senj County and for its association with the birthplace of inventor Nikola Tesla in nearby Smiljan.
  • B. Sevnica
    Sevnica is a small town in central Slovenia known as the childhood home of former U.S. First Lady Melania Trump.
  • C. Crikvenica
    Crikvenica is a coastal town and popular tourist resort on the Adriatic Sea in western Croatia.
  • D. Velenje
    Velenje is a modern industrial town in northern Slovenia known for its coal mining heritage, large lakeside recreational area, and one of the largest Tito statues in the world.
  • E. Kladno
    Kladno is an industrial city in the Czech Republic known historically for coal mining and steel production.
  • 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_69b345422aac81909ddbadae437d122e completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b351177eb88190b89fa49a88add5e8 completed March 12, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b6134ca4f88190a2aa34bf39d71ac6 completed March 15, 2026, 2:02 a.m.
Created at: March 12, 2026, 11:13 p.m.