Triple

T18035495
Position Surface form Disambiguated ID Type / Status
Subject Gatchinsky District E431497 entity
Predicate governingBodyLocatedIn P62 FINISHED
Object Gatchina NE NERFINISHED

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: [Gatchinsky District, governingBodyLocatedIn, Gatchina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gatchina
Context triple: [Gatchinsky District, governingBodyLocatedIn, 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. Ivangorod
    Ivangorod is a Russian border town on the Narva River, known for its medieval fortress facing the Estonian city of Narva.
  • C. Staraya Russa
    Staraya Russa is a historic town in northwestern Russia known for its medieval heritage and mineral spa resorts.
  • D. Vsevolozhsk
    Vsevolozhsk is a town in northwestern Russia that serves as an important suburban and administrative center near Saint Petersburg.
  • E. Torzhok
    Torzhok is a historic town in western Russia known for its medieval architecture, traditional goldwork embroidery, and location on the Tvertsa River.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d8b9050fb48190890155145deb0a66 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4be39a7348190a75735fe56c78fc3 completed April 19, 2026, 11:36 a.m.
Created at: April 10, 2026, 10:25 a.m.