Triple

T16017253
Position Surface form Disambiguated ID Type / Status
Subject North Kynouria E388498 entity
Predicate containsSettlement P847 FINISHED
Object Ano Vervena E1191704 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: Ano Vervena | Statement: [North Kynouria, containsSettlement, Ano Vervena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ano Vervena
Context triple: [North Kynouria, containsSettlement, Ano Vervena]
  • A. Ano Vervena chosen
    Ano Vervena is a small mountain village in the municipality of North Kynouria in the Arcadia region of the Peloponnese, Greece.
  • B. Kato Vervena
    Kato Vervena is a village in the municipality of North Kynouria in the Arcadia regional unit of the Peloponnese, Greece.
  • C. Verdolagas
    Verdolagas is the popular nickname of Honduran football club Marathón, one of the country’s most traditional and successful teams.
  • D. Verver
    Verver is the surname of Maggie Verver, a central character in Henry James’s novel "The Golden Bowl."
  • E. Schildkraut
    Schildkraut is a surname most notably associated with Austrian-American actor Joseph Schildkraut, an Academy Award winner known for his work in early 20th-century film and theater.
  • 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_69d86dabcb7c8190b6a39d6831d2fa1b completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e18295c6a4819093263db8669d4b08 completed April 17, 2026, 12:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffeb867ae88190945af88247d4c80b completed May 10, 2026, 2:20 a.m.
Created at: April 10, 2026, 4:55 a.m.