Triple

T10318697
Position Surface form Disambiguated ID Type / Status
Subject Akmola E242084 entity
Predicate previousName P65 FINISHED
Object Tselinograd E308846 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: Tselinograd | Statement: [Akmola, previousName, Tselinograd]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tselinograd
Context triple: [Akmola, previousName, Tselinograd]
  • A. Tselinograd chosen
    Tselinograd was the Soviet-era name of Kazakhstan’s capital city, now known as Astana.
  • B. Dimitrovgrad
    Dimitrovgrad is a Bulgarian industrial city in the south-central part of the country, known for its post-World War II planned urban layout and location in the Upper Thracian Plain.
  • C. Dimitrovgrad
    Dimitrovgrad is a major industrial and scientific city in Russia, known especially for its nuclear research facilities and machine-building industries.
  • D. Kirovgrad
    Kirovgrad is a small industrial town in Russia’s Ural region, historically associated with non-ferrous metal mining and processing.
  • E. Kuibyshev
    Kuibyshev is the former Soviet name of the Russian city now known as Samara, a major industrial and administrative center on the Volga River.
  • 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_69d381ac38808190a8ca7457c85b625b completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d35e019081909cc296d73227a3ed completed April 7, 2026, 9:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69dbb6cbdd30819087c3d980ab68c44e completed April 12, 2026, 3:14 p.m.
Created at: April 6, 2026, 11:49 a.m.