Triple

T9726183
Position Surface form Disambiguated ID Type / Status
Subject Tsaritsyno E235617 entity
Predicate servesArea P82 FINISHED
Object Tsaritsyno District E891461 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: Tsaritsyno District | Statement: [Tsaritsyno, servesArea, Tsaritsyno District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tsaritsyno District
Context triple: [Tsaritsyno, servesArea, Tsaritsyno District]
  • A. Tsaritsyno District chosen
    Tsaritsyno District is a residential and historical administrative area in southern Moscow, known for the nearby Tsaritsyno Palace and park complex.
  • B. Butyrsky District
    Butyrsky District is a residential and historically industrial administrative district in the north of Moscow, Russia.
  • C. Pereslavsky District
    Pereslavsky District is an administrative district in Yaroslavl Oblast, Russia, centered around the historic town of Pereslavl-Zalessky.
  • D. Nevelsky District
    Nevelsky District is an administrative and municipal district in western Russia, located within Pskov Oblast and centered around the town of Nevel.
  • E. Gatchinsky District
    Gatchinsky District is an administrative and municipal district in northwestern Russia known for its historical town of Gatchina and proximity to Saint Petersburg.
  • 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_69ca84d0fad481909cdd45aa77416c48 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9e798c348190885b79d7dffc9d8d completed April 1, 2026, 10:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69e15435faa881909b1a124f8027deeb completed April 16, 2026, 9:27 p.m.
Created at: March 30, 2026, 8:21 p.m.