Triple

T16066282
Position Surface form Disambiguated ID Type / Status
Subject Kaluga offensive operation E389739 entity
Predicate location P40 FINISHED
Object Kaluga 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: Kaluga | Statement: [Kaluga offensive operation, location, Kaluga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kaluga
Context triple: [Kaluga offensive operation, location, Kaluga]
  • A. Kaluga chosen
    Kaluga is a historic city in western Russia known as a regional administrative center and an important site in several Russian uprisings and military campaigns.
  • B. Kirov
    Kirov is the revolutionary pseudonym of Sergei Kirov, a prominent early Soviet political leader and close associate of Joseph Stalin.
  • C. Kirov
    Kirov is a town in Kaluga Oblast, Russia, known as a local administrative and industrial center.
  • D. Kirov
    Kirov is a Soviet nuclear-powered guided-missile battlecruiser that served as the lead ship of one of the largest and most heavily armed surface combatant classes built since World War II.
  • E. Sverdlovsk
    Sverdlovsk is the former name of Yekaterinburg, a major industrial and cultural city in Russia’s Ural region.
  • 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_69d86daf32ec8190a8c0466c8f49c3c0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1837ca628819081dfc439fe322d58 completed April 17, 2026, 12:49 a.m.
Created at: April 10, 2026, 4:57 a.m.