Triple

T13129743
Position Surface form Disambiguated ID Type / Status
Subject Vyborgsky District E311936 entity
Predicate containsSettlement P847 FINISHED
Object Parnas E617242 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: Parnas | Statement: [Vyborgsky District, containsSettlement, Parnas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Parnas
Context triple: [Vyborgsky District, containsSettlement, Parnas]
  • A. Parnas chosen
    Parnas is a metro station in Saint Petersburg, Russia, serving as the northern terminus of one of the city’s subway lines.
  • B. Yarshater
    Yarshater is the surname of Ehsan Yarshater, a prominent Iranian historian and founding editor of the Encyclopaedia Iranica.
  • C. Kalmus
    Kalmus is a surname most notably associated with Herbert Kalmus, the co-founder of the pioneering color motion picture company Technicolor.
  • D. Tatischeff
    Tatischeff is the original family surname of French filmmaker and actor Jacques Tati, known for his influential comedic films and the character Monsieur Hulot.
  • E. Prochiantz
    Prochiantz is the surname of Alain Prochiantz, a prominent French neuroscientist known for his work on brain development and homeoprotein signaling.
  • 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_69d806a9fe888190b081e2d9ea665d6c completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9819bfd348190a22d44f837877e1c completed April 10, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6e290c308819090ee4436c199b57c completed May 3, 2026, 5:52 a.m.
Created at: April 9, 2026, 9:07 p.m.