Triple

T6194280
Position Surface form Disambiguated ID Type / Status
Subject Kvarner Gulf E138470 entity
Predicate hasResortTown P847 FINISHED
Object Opatija E319761 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: Opatija | Statement: [Kvarner Gulf, hasResortTown, Opatija]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Opatija
Context triple: [Kvarner Gulf, hasResortTown, Opatija]
  • A. Opatija chosen
    Opatija is a historic seaside resort town on Croatia’s Adriatic coast, known for its elegant Austro-Hungarian architecture, mild climate, and long tradition of tourism.
  • B. Šibenik
    Šibenik is a historic coastal city in Croatia known for its medieval architecture and the UNESCO-listed Cathedral of St. James.
  • C. Zadar
    Zadar is a historic coastal city in Croatia on the Adriatic Sea, known for its Roman and Venetian ruins, medieval churches, and modern seaside installations like the Sea Organ.
  • 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. Koprivnica
    Koprivnica is a city in northern Croatia known as a regional center of the Podravina area, with historical roots dating back to medieval times and a strong tradition in industry and culture.
  • 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_69c008ab9b3081908a11b2c744838435 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062443cec81909dc9bafea2f5e7d4 completed March 22, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c723a7e26c8190bdd0dd476eac3492 completed March 28, 2026, 12:41 a.m.
Created at: March 22, 2026, 4:19 p.m.