Triple

T18814813
Position Surface form Disambiguated ID Type / Status
Subject Njivice E460107 entity
Predicate nearbySettlement P350 FINISHED
Object Krk (town) NE NERFINISHED

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: Krk (town) | Statement: [Njivice, nearbySettlement, Krk (town)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Krk (town)
Context triple: [Njivice, nearbySettlement, Krk (town)]
  • A. Krk chosen
    Krk is a large Adriatic Sea island in the northern part of Croatia, known for its historic towns, beaches, and popular tourist resorts.
  • B. Krupanj
    Krupanj is a small town in western Serbia known for its mountainous surroundings, mining history, and role in World War I.
  • C. Krnjak
    Krnjak is a small municipality and village located in central Croatia, known for its rural character and mixed ethnic population.
  • D. Donji Kraljevec
    Donji Kraljevec is a village in northern Croatia best known as the birthplace of philosopher and esotericist Rudolf Steiner.
  • E. Klanjec
    Klanjec is a small town in northern Croatia’s Zagorje region, known for its historic architecture and picturesque rural surroundings.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d398c7d4819091cb2f7e48948aeb completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5a3df2d3881909b336d813bbfd0aa completed April 20, 2026, 3:56 a.m.
Created at: April 10, 2026, 11:53 a.m.