Triple

T15534389
Position Surface form Disambiguated ID Type / Status
Subject Kremlings E370304 entity
Predicate hasSubgroup P747 FINISHED
Object Kannon-type Kremlings E370304 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: Kannon-type Kremlings | Statement: [Kremlings, hasSubgroup, Kannon-type Kremlings]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kannon-type Kremlings
Context triple: [Kremlings, hasSubgroup, Kannon-type Kremlings]
  • A. Kremlings chosen
    Kremlings are a recurring race of crocodilian villains in the Donkey Kong video game series, often serving as the primary antagonists led by King K. Rool.
  • B. Tsalka
    Tsalka is a town in southern Georgia known for its ethnically diverse population and its location near the Tsalka Reservoir in the Kvemo Kartli region.
  • C. Gorky-130
    Gorky-130 was the Soviet-era codename for the closed nuclear research city now known as Sarov in Russia.
  • D. Konenkov
    Konenkov is a Russian surname most notably associated with the sculptor Sergey Konenkov, often called the "Russian Rodin."
  • E. OSK Brestsky
    OSK Brestsky is a multi-purpose football stadium in Brest, Belarus, best known as the home ground of FC Dynamo Brest.
  • 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_69d85cc521a08190921fb50319dddc34 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e0442e327c8190b4b879c8a3cd38e3 completed April 16, 2026, 2:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff4c39ffbc819089cea285e8145fa4 completed May 9, 2026, 3:01 p.m.
Created at: April 10, 2026, 4:06 a.m.