Triple

T9860169
Position Surface form Disambiguated ID Type / Status
Subject Bibirevo E239688 entity
Predicate namedAfter P63 FINISHED
Object Bibirevo District E828772 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: Bibirevo District | Statement: [Bibirevo, namedAfter, Bibirevo District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bibirevo District
Context triple: [Bibirevo, namedAfter, Bibirevo District]
  • A. Bibirevo District chosen
    Bibirevo District is a residential administrative district in the North-Eastern Administrative Okrug of Moscow, Russia, known for its large housing estates and urban infrastructure.
  • B. Bikinsky District
    Bikinsky District is an administrative and municipal district in Khabarovsk Krai in Russia, known for its rural localities and position in the Russian Far East.
  • C. Ramenki District
    Ramenki District is a residential and educational area in western Moscow, known for its universities, green spaces, and proximity to major city transport routes.
  • D. Gusu District
    Gusu District is the central urban district of Suzhou, China, known for its historic canals, classical gardens, and well-preserved ancient cityscape.
  • E. Shimanovsky District
    Shimanovsky District is an administrative district in Amur Oblast, Russia, centered around the town of Shimanovsk.
  • 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_69ca84e6493081909cf58c8d42ea856b completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb3b582cc81909a6d638fe2573c43 completed April 2, 2026, 12:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69d23cfc50948190aae82dced585fa29 completed April 5, 2026, 10:44 a.m.
Created at: March 30, 2026, 8:35 p.m.