Triple

T6688681
Position Surface form Disambiguated ID Type / Status
Subject Budong-Budong language E152166 entity
Predicate hasAlternativeName P39 FINISHED
Object Budong-Budong E610796 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: Budong-Budong | Statement: [Budong-Budong language, hasAlternativeName, Budong-Budong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Budong-Budong
Context triple: [Budong-Budong language, hasAlternativeName, Budong-Budong]
  • A. Budongbudong chosen
    Budongbudong is an Austronesian language spoken by a small community in Sulawesi, Indonesia.
  • B. Dogok-dong
    Dogok-dong is a residential neighborhood in Seoul, South Korea, known for its affluent apartment complexes and location within the upscale Gangnam area.
  • C. Bugaloo
    Bugaloo is a minor character in the 1994 basketball-themed drama film "Above the Rim."
  • D. Bugotu
    Bugotu is an Austronesian language of the Meso-Melanesian subgroup spoken primarily on Santa Isabel Island in the Solomon Islands.
  • E. Kabu Kabu
    Kabu Kabu is a speculative fiction short story collection by Nnedi Okorafor that blends African folklore, magical realism, and contemporary themes.
  • 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_69c687f9977c819097e7f5ada4fe522e completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b14feb28819097bc157df8a2f96e completed March 27, 2026, 4:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7007ad59c8190a752d9b1152c3435 completed March 27, 2026, 10:11 p.m.
Created at: March 27, 2026, 2:04 p.m.