Triple

T4346449
Position Surface form Disambiguated ID Type / Status
Subject Nikola Tesla Memorial Center E97914 entity
Predicate near P350 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: [Nikola Tesla Memorial Center, near, Gospić]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gospić
Context triple: [Nikola Tesla Memorial Center, near, 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_69b34548402c819085ab68b27c235a87 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3518d6728819084a2f40ae0bd3ac8 completed March 12, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b6373b66a481909f66ea8b8659d54a completed March 15, 2026, 4:36 a.m.
Created at: March 12, 2026, 11:15 p.m.