Triple

T10066169
Position Surface form Disambiguated ID Type / Status
Subject Urang Kanekes E213106 entity
Predicate selfDesignation P974 FINISHED
Object Urang Kanekes E213106 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: Urang Kanekes | Statement: [Urang Kanekes, selfDesignation, Urang Kanekes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Urang Kanekes
Context triple: [Urang Kanekes, selfDesignation, Urang Kanekes]
  • A. Urang Kanekes chosen
    Urang Kanekes are an indigenous Sundanese community in Banten, Indonesia, known for their Baduy identity and traditional, highly secluded way of life.
  • B. Kanemoto
    Kanemoto is a Japanese surname most notably associated with former professional baseball player and manager Tomonori Kanemoto.
  • C. Nezu
    Nezu is a traditional neighborhood in Tokyo known for its historic Nezu Shrine, old-town atmosphere, and preserved shitamachi streets.
  • D. Takaishi
    Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
  • E. Warekena
    The Warekena are an Indigenous people of the Amazon region, primarily living along rivers in Brazil and Venezuela, known for their distinct Arawakan language and traditional riverine lifestyle.
  • 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_69ca83977128819084084eb7d1d8c52a completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdcff51b108190b6759f651d4ba2d2 completed April 2, 2026, 2:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2b630ca008190a337660ad8c9d57e completed April 5, 2026, 7:21 p.m.
Created at: March 30, 2026, 8:58 p.m.