Triple

T10899194
Position Surface form Disambiguated ID Type / Status
Subject Buru Island E257390 entity
Predicate hasLanguage P15 FINISHED
Object Buru language E652717 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: Buru language | Statement: [Buru Island, hasLanguage, Buru language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Buru language
Context triple: [Buru Island, hasLanguage, Buru language]
  • A. Buru languages chosen
    Buru languages are a small group of closely related Austronesian languages spoken primarily on Buru Island in Indonesia’s Maluku region.
  • B. Bura language
    Bura language is a Chadic language spoken primarily in northeastern Nigeria by the Bura people.
  • C. Bunak language
    The Bunak language is a Papuan language spoken primarily in the central region of Timor, straddling the border between Indonesia and Timor-Leste.
  • D. Embaloh language
    The Embaloh language is an Austronesian language spoken by the Embaloh people of West Kalimantan in Borneo, Indonesia.
  • E. Bima language
    Bima language is an Austronesian language spoken primarily on Sumbawa Island in Indonesia, known for its distinct grammar and vocabulary within the region.
  • 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_69d6aa8550c8819095508a2ed9acf3db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d761a2392c8190bc2c2359d63eff7a completed April 9, 2026, 8:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69e15524ec5c8190a330ce5fc16dd11d completed April 16, 2026, 9:31 p.m.
Created at: April 8, 2026, 9:21 p.m.