Triple

T22300885
Position Surface form Disambiguated ID Type / Status
Subject Wajo dialect E551250 entity
Predicate parentLanguage P32053 FINISHED
Object Bugis language 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: Bugis language | Statement: [Wajo dialect, parentLanguage, Bugis language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bugis language
Context triple: [Wajo dialect, parentLanguage, Bugis language]
  • A. Buginese language chosen
    Buginese language is an Austronesian language spoken primarily by the Bugis people of South Sulawesi, Indonesia, known for its traditional Lontara script and rich literary heritage.
  • B. Kayabí language
    The Kayabí language is an indigenous Tupian language spoken by the Kayabí people of Brazil, known for its role in preserving their cultural and linguistic heritage.
  • C. Bugotu language
    The Bugotu language is an Oceanic language spoken by the Bugotu people of Santa Isabel Island in the Solomon Islands.
  • D. Badimaya language
    Badimaya language is an Australian Aboriginal language traditionally spoken by the Yamatji people of Western Australia.
  • E. Sawunese language
    The Sawunese language is an Austronesian language spoken primarily on Savu (Sawu) Island in eastern Indonesia.
  • 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_69e11e46c0188190800181a4233f28fe completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f1572399148190853c4e91fcf9f38c completed April 29, 2026, 12:56 a.m.
Created at: April 16, 2026, 8:41 p.m.