Triple

T7081722
Position Surface form Disambiguated ID Type / Status
Subject Sulawesi languages E164970 entity
Predicate include P1393 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: [Sulawesi languages, include, Bugis language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bugis language
Context triple: [Sulawesi languages, include, 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. Sawunese language
    The Sawunese language is an Austronesian language spoken primarily on Savu (Sawu) Island in eastern Indonesia.
  • E. Yaeyama language
    The Yaeyama language is a Southern Ryukyuan language spoken in Japan’s Yaeyama Islands, distinct from standard Japanese and recognized as endangered.
  • 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_69c6887cbc6c8190bdfac42d940f4d8a completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e4f1f5748190b214856bcfc70d81 completed March 27, 2026, 8:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c79477a79c81909b51175a24d17142 completed March 28, 2026, 8:42 a.m.
Created at: March 27, 2026, 2:40 p.m.