Triple

T3108109
Position Surface form Disambiguated ID Type / Status
Subject Voronezh–Voroshilovgrad defensive operations E64882 entity
Predicate namedAfter P63 FINISHED
Object Voroshilovgrad E279036 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: Voroshilovgrad | Statement: [Voronezh–Voroshilovgrad defensive operations, namedAfter, Voroshilovgrad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Voroshilovgrad
Context triple: [Voronezh–Voroshilovgrad defensive operations, namedAfter, Voroshilovgrad]
  • A. Dimitrovgrad
    Dimitrovgrad is a major industrial and scientific city in Russia, known especially for its nuclear research facilities and machine-building industries.
  • B. Tselinograd
    Tselinograd was the Soviet-era name of Kazakhstan’s capital city, now known as Astana.
  • C. Krasnoarmeysk
    Krasnoarmeysk is a town in southwestern Russia known as one of the urban centers of Saratov Oblast.
  • D. Alchevsk chosen
    Alchevsk is an industrial city in eastern Ukraine known for its steel and metallurgical plants.
  • E. Chapaevsk
    Chapaevsk is an industrial city in southwestern Russia known for its chemical industry and location within Samara Oblast along the Volga River region.
  • 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_69ad857eeaf48190b34ebfdaa7a264cf completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada29eacc88190a19c5ca8e53e3dca completed March 8, 2026, 4:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b732a05c81908fea7f9292ba87d5 completed March 14, 2026, 7:29 p.m.
Created at: March 8, 2026, 3:04 p.m.