Triple

T23307360
Position Surface form Disambiguated ID Type / Status
Subject Baduy people E590486 entity
Predicate autonym P1435 FINISHED
Object Urang Kanekes 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: Urang Kanekes | Statement: [Baduy people, autonym, Urang Kanekes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Urang Kanekes
Context triple: [Baduy people, autonym, 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. Kamekura
    Kamekura is a Japanese surname most notably associated with Yūsaku Kamekura, a pioneering graphic designer known for his influential modernist posters and logos.
  • 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_69e25d1c0ecc8190a355aa229f06d0e0 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1972846fc819092ca2b9590b2e177 completed April 29, 2026, 5:29 a.m.
Created at: April 17, 2026, 5:05 p.m.