Triple

T17750157
Position Surface form Disambiguated ID Type / Status
Subject Gmina Bukowina Tatrzańska E443090 entity
Predicate hasPart P35 FINISHED
Object Czarna Góra 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: Czarna Góra | Statement: [Gmina Bukowina Tatrzańska, hasPart, Czarna Góra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Czarna Góra
Context triple: [Gmina Bukowina Tatrzańska, hasPart, Czarna Góra]
  • A. Czarna Góra chosen
    Czarna Góra is a village in southern Poland, known as a mountain resort area in the Tatra region.
  • B. Vidova Gora
    Vidova Gora is a prominent mountain peak on the Croatian island of Brač, known for its sweeping views over the Adriatic Sea and nearby islands.
  • C. Ravna Gora
    Ravna Gora is a small mountain town in Croatia’s forested Gorski Kotar region, known for its natural landscapes and outdoor recreation.
  • D. Goč Mountain
    Goč Mountain is a forested mountain in central Serbia known for its hiking trails, ski slopes, and proximity to the city of Kraljevo.
  • E. Kosmaj Mountain
    Kosmaj Mountain is a low, forested mountain in central Serbia known for its scenic landscapes, historical monuments, and proximity to Belgrade.
  • 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48418c0188190beb31809b40e4648 completed April 19, 2026, 7:28 a.m.
Created at: April 10, 2026, 10:10 a.m.