Triple

T4361779
Position Surface form Disambiguated ID Type / Status
Subject Philhellenes E98676 entity
Predicate hasNotableMember P304 FINISHED
Object Gogol E23344 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: Gogol | Statement: [Philhellenes, hasNotableMember, Gogol]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gogol
Context triple: [Philhellenes, hasNotableMember, Gogol]
  • A. Nikolai Gogol chosen
    Nikolai Gogol was a 19th-century Russian-language writer of Ukrainian origin, renowned for his influential satirical and surreal works such as "Dead Souls" and "The Overcoat."
  • B. Dr. Gogol
    Dr. Gogol is the obsessive, deranged surgeon and main antagonist in the 1935 horror film "Mad Love," known for his macabre experiments and fixation on a famous actress.
  • C. Pyotr Saltykov
    Pyotr Saltykov was an 18th-century Russian field marshal best known for leading Russian forces to a decisive victory over Prussia during the Seven Years' War.
  • D. Rafail Ostrovsky
    Rafail Ostrovsky is a prominent computer scientist known for his influential contributions to cryptography, secure computation, and theoretical computer science.
  • E. Gorky
    Gorky is the former name of the Russian city of Nizhny Novgorod, historically known as a closed city in the Soviet era and a site of internal exile for dissidents.
  • 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_69b3454c772081908e20173e379e8ebe completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b351e47d388190b31500189577cd75 completed March 12, 2026, 11:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5e504f7b88190abc3e999c499920d completed March 14, 2026, 10:45 p.m.
Created at: March 12, 2026, 11:16 p.m.