Triple

T22621391
Position Surface form Disambiguated ID Type / Status
Subject Akawaio E558288 entity
Predicate hasAlternativeName P39 FINISHED
Object Kapon NE NERFINISHED

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: Kapon | Statement: [Akawaio, hasAlternativeName, Kapon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kapon
Context triple: [Akawaio, hasAlternativeName, Kapon]
  • A. Kapon chosen
    Kapon is an indigenous language (also known as Akawaio) spoken by the Akawaio people of the Guiana Highlands in northern South America.
  • B. Kittin
    Kittin is a French DJ, producer, and singer known for her influential role in the electroclash and techno scenes.
  • C. Kotek
    Kotek is the surname of Tina Kotek, an American politician who has served as Governor of Oregon and previously as Speaker of the Oregon House of Representatives.
  • D. Kanne
    Kanne is a village in the municipality of Riemst in the Belgian province of Limburg, known for its historic fortifications and location near the Dutch border.
  • E. Kutton
    Kutton is a scenic mountain village and popular tourist spot in Pakistan-administered Azad Kashmir, known for its lush green landscapes, waterfalls, and cool climate.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e24545a8e08190bfa7482a2c725ff1 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f16e39959481909e0ae67379435f95 completed April 29, 2026, 2:34 a.m.
Created at: April 17, 2026, 3 p.m.