Triple

T18779106
Position Surface form Disambiguated ID Type / Status
Subject Gmina Gubin E459207 entity
Predicate administrativeCenter P1474 FINISHED
Object Gubin 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: Gubin | Statement: [Gmina Gubin, administrativeCenter, Gubin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gubin
Context triple: [Gmina Gubin, administrativeCenter, Gubin]
  • A. Gubin chosen
    Gubin is a town in western Poland situated on the Lusatian Neisse River, directly opposite the German town of Guben, forming a cross-border urban area.
  • B. Gubakha
    Gubakha is a small industrial town in Russia’s Perm Krai, historically associated with coal mining and chemical production in the Ural region.
  • C. Gongjin
    Gongjin is the courtesy name of Zhou Yu, a renowned Eastern Han dynasty military general and strategist best known for his role in the Battle of Red Cliffs.
  • D. Gubongsan
    Gubongsan is a mountain located in or near the city of Daejeon in South Korea, known for its hiking trails and scenic views.
  • E. Kwangde
    Kwangde is a prominent Himalayan mountain massif in Nepal’s Khumbu region, known for its steep faces and challenging climbing routes.
  • 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_69d8d396f54c8190ba49db31e8743842 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5933d2d048190a42480edc70bf086 completed April 20, 2026, 2:45 a.m.
Created at: April 10, 2026, 11:52 a.m.