Triple

T17525722
Position Surface form Disambiguated ID Type / Status
Subject Liozna E426790 entity
Predicate isSeatOf P62 FINISHED
Object Liozna District 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: Liozna District | Statement: [Liozna, isSeatOf, Liozna District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Liozna District
Context triple: [Liozna, isSeatOf, Liozna District]
  • A. Liozna District chosen
    Liozna District is an administrative district (raion) in the Vitebsk Region of northeastern Belarus, known for its rural settlements and historical ties to the town of Liozna.
  • B. Pytalovsky District
    Pytalovsky District is an administrative and municipal district in western Russia, located in the border region of Pskov Oblast near Latvia.
  • C. Lazovsky District
    Lazovsky District is an administrative district in Primorsky Krai, Russia, known for its rugged coastal landscapes and the Lazovsky Nature Reserve on the Sea of Japan.
  • D. Kuzminki District
    Kuzminki District is an administrative district (raion) of Moscow, Russia, known for its large Kuzminki Park and residential neighborhoods.
  • E. Leshukonsky District
    Leshukonsky District is a sparsely populated administrative district in Arkhangelsk Oblast, Russia, known for its remote northern location, taiga landscapes, and traditional rural settlements.
  • 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_69d889de677081909b22d2657b1f0292 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e452d6a2548190acf26f2d5d4aab66 completed April 19, 2026, 3:58 a.m.
Created at: April 10, 2026, 5:49 a.m.