Triple

T13417447
Position Surface form Disambiguated ID Type / Status
Subject Maros Regency E313248 entity
Predicate localLanguages P10892 FINISHED
Object Bugis language E128374 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: Bugis language | Statement: [Maros Regency, localLanguages, Bugis language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bugis language
Context triple: [Maros Regency, localLanguages, 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 (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_69d806ad0c44819088833ae1ec9e9690 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaeb8416c8190a00dde0917c26f51 completed April 12, 2026, 2:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69f73987cc088190839e8a589086639c completed May 3, 2026, 12:03 p.m.
Created at: April 9, 2026, 9:39 p.m.