Triple

T5944385
Position Surface form Disambiguated ID Type / Status
Subject Kingdom of Wajo E132242 entity
Predicate language P15 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: [Kingdom of Wajo, language, Bugis language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bugis language
Context triple: [Kingdom of Wajo, language, 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_69c00869d3308190af89b2453e0f7546 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c03937b4a88190819a1fd63fc3d3ed completed March 22, 2026, 6:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0c084fce481909c306d6eeb99066d completed March 23, 2026, 4:24 a.m.
Created at: March 22, 2026, 4:01 p.m.