Triple

T16770462
Position Surface form Disambiguated ID Type / Status
Subject Hajnówka E407578 entity
Predicate hasTwinTown P919 FINISHED
Object Klimavichy E958981 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: Klimavichy | Statement: [Hajnówka, hasTwinTown, Klimavichy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Klimavichy
Context triple: [Hajnówka, hasTwinTown, Klimavichy]
  • A. Klimavichy chosen
    Klimavichy is a small town in eastern Belarus known for its location within the Mogilev Region and its role as a local administrative and cultural center.
  • B. Klimczok
    Klimczok is a prominent mountain peak in southern Poland, located in the Silesian Beskids range and popular for hiking and winter sports.
  • C. Kühtai
    Kühtai is a high-altitude ski resort village in the Austrian Alps known for its winter sports facilities and reliable snow conditions.
  • D. Olgovichi
    Olgovichi were a prominent princely branch of the Rurikid dynasty that ruled various principalities in medieval Kievan Rus, particularly centered around Chernigov.
  • E. Biegun
    Biegun is a Polish surname borne by various individuals, including figures in politics, academia, and the arts.
  • 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_69d8839174188190909f190097207065 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b0361e5081908f58edf766ff3ce0 completed April 18, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00a5361c3881909be0fb9b83a59993 completed May 10, 2026, 3:33 p.m.
Created at: April 10, 2026, 5:21 a.m.