Triple

T14151939
Position Surface form Disambiguated ID Type / Status
Subject Silozi E350703 entity
Predicate influencedBy P9 FINISHED
Object Luyana E252594 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: Luyana | Statement: [Silozi, influencedBy, Luyana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luyana
Context triple: [Silozi, influencedBy, Luyana]
  • A. Luyana chosen
    Luyana is a Bantu language of southwestern Africa that historically served as a prestige and source language for the development of the Lozi language.
  • B. Mirafra
    Mirafra is a genus of small, ground-dwelling larks known for their cryptic plumage and elaborate song displays, found mainly in Africa and parts of Asia.
  • C. Lalan
    Lalan was a Chinese-born French painter, composer, and dancer known for her abstract, lyrical works and her close association with the postwar Paris art scene.
  • D. Nayapala
    Nayapala was a ruler of the Pala dynasty in eastern India, known for consolidating Pala power in Bengal and Bihar during the 11th century.
  • E. Luyanó
    Luyanó is a traditional working-class neighborhood in Havana, Cuba, known for its dense urban fabric and vibrant local culture.
  • 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_69d8278775fc8190b0802d22ca2f495d completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6124e23481909e5132a40a1d8624 completed April 14, 2026, 3:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcf7ea34408190830263d7f5a88ce9 completed May 7, 2026, 8:36 p.m.
Created at: April 10, 2026, 12:57 a.m.