Triple

T11846648
Position Surface form Disambiguated ID Type / Status
Subject Danilov E281794 entity
Predicate partOf P40 FINISHED
Object Danilovsky District E586933 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: Danilovsky District | Statement: [Danilov, partOf, Danilovsky District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Danilovsky District
Context triple: [Danilov, partOf, Danilovsky District]
  • A. Danilovsky District chosen
    Danilovsky District is a central administrative district of Moscow, Russia, known for its historic religious sites, including the Danilov Monastery, and its mix of residential, cultural, and commercial areas.
  • B. Kalachyovsky District
    Kalachyovsky District is an administrative district in Volgograd Oblast, Russia, known for encompassing the town of Kalach-na-Donu and its surrounding rural areas.
  • C. Gagarinsky District
    Gagarinsky District is an administrative district in Moscow, Russia, known for its residential areas, educational institutions, and major transport routes.
  • D. Nikolaevsky District
    Nikolaevsky District is an administrative and municipal district located within Khabarovsk Krai in the Russian Far East.
  • E. Yurinsky District
    Yurinsky District is an administrative and municipal district in the Mari El Republic of Russia, characterized by its rural settlements and small population.
  • 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_69d6ab287ba48190a5178779fd19b9b7 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a65b5ff08190bb58361f6a6acdca completed April 10, 2026, 7:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69f72654dc88819095bc1ce23dfee4df completed May 3, 2026, 10:41 a.m.
Created at: April 8, 2026, 9:43 p.m.