Triple

T8011557
Position Surface form Disambiguated ID Type / Status
Subject Moscow Governorate E186504 entity
Predicate hasMajorCity P316 FINISHED
Object Dmitrov E55627 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: Dmitrov | Statement: [Moscow Governorate, hasMajorCity, Dmitrov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dmitrov
Context triple: [Moscow Governorate, hasMajorCity, Dmitrov]
  • A. Dmitrov chosen
    Dmitrov is a historic town in Moscow Oblast, Russia, located north of Moscow and known for its medieval kremlin and role as a regional cultural center.
  • B. Serpukhov
    Serpukhov is a historic Russian town south of Moscow known for its medieval monasteries, industrial heritage, and location on the Nara River.
  • C. Balashov
    Balashov is a town in southwestern Russia that serves as an important local administrative and transportation center within Saratov Oblast.
  • D. Elektrostal
    Elektrostal is an industrial city in Russia known for its metallurgical and engineering industries, located east of Moscow.
  • E. Podolsk
    Podolsk is a major industrial city and former center of machine-building located just south of Moscow in western Russia.
  • 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_69ca82abaffc8190ab8af79cdbc31ab3 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3d722fbc8190b22745b581421f16 completed March 31, 2026, 3:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfeaaf9ea0819091bd0981068e5a72 completed April 3, 2026, 4:28 p.m.
Created at: March 30, 2026, 5:19 p.m.