Triple

T1766846
Position Surface form Disambiguated ID Type / Status
Subject Leningrad Oblast E38781 entity
Predicate administrativeCenter P1474 FINISHED
Object Gatchina E138901 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: Gatchina | Statement: [Leningrad Oblast, administrativeCenter, Gatchina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gatchina
Context triple: [Leningrad Oblast, administrativeCenter, Gatchina]
  • A. Gatchina chosen
    Gatchina is a historic Russian town near Saint Petersburg, known for its imperial palace complex and long association with the Romanov dynasty.
  • B. Kostroma
    Kostroma is a historic Russian city northeast of Moscow, known as part of the Golden Ring and for its well-preserved medieval architecture and monasteries.
  • C. Petergof
    Petergof is a historic Russian town near Saint Petersburg, renowned for its grand imperial palaces, elaborate fountains, and landscaped parks along the Gulf of Finland.
  • D. Shlisselburg
    Shlisselburg is a historic Russian town near Saint Petersburg, best known for its strategic fortress and former political prison on Lake Ladoga.
  • E. Kolomna
    Kolomna is a historic Russian city southeast of Moscow, known for its well-preserved kremlin, medieval architecture, and traditional pastila confectionery.
  • 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_69a8862d562481908d7025a1c1f67c0d completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa646914048190bbe282a3d4768835 completed March 6, 2026, 5:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae26ee4c088190a767d71f1a68a734 completed March 9, 2026, 1:48 a.m.
Created at: March 4, 2026, 7:31 p.m.