Triple

T12755874
Position Surface form Disambiguated ID Type / Status
Subject Dmitrovsky District E304857 entity
Predicate hasHistoricCenter P295 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: [Dmitrovsky District, hasHistoricCenter, Dmitrov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dmitrov
Context triple: [Dmitrovsky District, hasHistoricCenter, 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_69d7bdf1fcd081909ffb0e0d6fa3a07d completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96d8b57b88190b29b8fdca415c81c completed April 10, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6fefabc8081908e46ffcaef22cce1 completed May 3, 2026, 7:53 a.m.
Created at: April 9, 2026, 5:27 p.m.