Triple

T17769395
Position Surface form Disambiguated ID Type / Status
Subject Pinsk District E443592 entity
Predicate hasBorderWith P224 FINISHED
Object Luninets District NE NERFINISHED

How this triple was built (3 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: Luninets District | Statement: [Pinsk District, hasBorderWith, Luninets District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luninets District
Context triple: [Pinsk District, hasBorderWith, Luninets District]
  • A. Nanaysky District
    Nanaysky District is an administrative and municipal district in Khabarovsk Krai, Russia, known for its rural settlements along the Amur River and its indigenous Nanai population.
  • B. Ruzsky District
    Ruzsky District is an administrative and municipal district in Moscow Oblast, Russia, known for its mix of small towns, rural settlements, and historical sites west of Moscow.
  • C. Ulchsky District
    Ulchsky District is an administrative district in Khabarovsk Krai in Russia, located along the lower Amur River and known for its indigenous Ulch population and remote, sparsely populated territory.
  • D. 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.
  • E. Pytalovsky District
    Pytalovsky District is an administrative and municipal district in western Russia, located in the border region of Pskov Oblast near Latvia.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Luninets District
Target entity description: Luninets District is an administrative district (raion) in the Brest Region of Belarus, known for its agricultural landscape and location in the Polesia region.
  • A. Nanaysky District
    Nanaysky District is an administrative and municipal district in Khabarovsk Krai, Russia, known for its rural settlements along the Amur River and its indigenous Nanai population.
  • B. Ruzsky District
    Ruzsky District is an administrative and municipal district in Moscow Oblast, Russia, known for its mix of small towns, rural settlements, and historical sites west of Moscow.
  • C. Ulchsky District
    Ulchsky District is an administrative district in Khabarovsk Krai in Russia, located along the lower Amur River and known for its indigenous Ulch population and remote, sparsely populated territory.
  • D. 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.
  • E. Pytalovsky District
    Pytalovsky District is an administrative and municipal district in western Russia, located in the border region of Pskov Oblast near Latvia.
  • F. None of above. chosen

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_69d8b9edf16c8190a59ebd245d378f4f completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e485fe70648190b4107e1eabacc694 completed April 19, 2026, 7:36 a.m.
Created at: April 10, 2026, 10:11 a.m.