Triple

T6099073
Position Surface form Disambiguated ID Type / Status
Subject Laiyolo language E135948 entity
Predicate hasLoanwordsFrom P506 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: [Laiyolo language, hasLoanwordsFrom, Bugis language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bugis language
Context triple: [Laiyolo language, hasLoanwordsFrom, 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. Bugotu language
    The Bugotu language is an Oceanic language spoken by the Bugotu people of Santa Isabel Island in the Solomon Islands.
  • C. Sawunese language
    The Sawunese language is an Austronesian language spoken primarily on Savu (Sawu) Island in eastern Indonesia.
  • D. Yaeyama language
    The Yaeyama language is a Southern Ryukyuan language spoken in Japan’s Yaeyama Islands, distinct from standard Japanese and recognized as endangered.
  • E. Banggai language
    The Banggai language is an Austronesian language spoken by the Banggai people in the Banggai Islands and nearby coastal areas of Central Sulawesi, 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_69c0087cd3c48190b459848c72d84eb1 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05a9a02888190ac201acd14c3fc31 completed March 22, 2026, 9:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1358d0e18819084e2acb9e75271b4 completed March 23, 2026, 12:43 p.m.
Created at: March 22, 2026, 4:13 p.m.