Triple

T7196613
Position Surface form Disambiguated ID Type / Status
Subject Pico de Aneto E168630 entity
Predicate firstAscentBy P1321 FINISHED
Object Platon de Tchihatcheff E282617 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: Platon de Tchihatcheff | Statement: [Pico de Aneto, firstAscentBy, Platon de Tchihatcheff]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Platon de Tchihatcheff
Context triple: [Pico de Aneto, firstAscentBy, Platon de Tchihatcheff]
  • A. Platon de Tchihatcheff chosen
    Platon de Tchihatcheff was a 19th-century Russian military officer and mountaineer known for his pioneering ascents in the Pyrenees.
  • B. Platon Volkov
    Platon Volkov was the husband of Zinaida Volkova, the daughter of Russian revolutionary Leon Trotsky.
  • C. Platon Oyunsky
    Platon Oyunsky was a prominent Yakut (Sakha) writer, poet, and statesman who played a key role in the development of Sakha literature and culture in the early Soviet period.
  • D. Innokenty Smoktunovsky
    Innokenty Smoktunovsky was a renowned Soviet and Russian actor celebrated for his nuanced stage and film performances, including his iconic portrayal of Hamlet.
  • E. Nikolai Podvoisky
    Nikolai Podvoisky was a Bolshevik revolutionary and Soviet political figure who played a key role in organizing the October Revolution and early Red Army structures.
  • 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_69c68a5376748190bb500f03df86e93e completed March 27, 2026, 1:46 p.m.
NER Named-entity recognition batch_69c6e928ecdc8190a7f3feaf6d28781b completed March 27, 2026, 8:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7bfa14e1c8190968b207bef0c96a9 completed March 28, 2026, 11:46 a.m.
Created at: March 27, 2026, 2:51 p.m.