Triple

T15497719
Position Surface form Disambiguated ID Type / Status
Subject Bura people E378863 entity
Predicate language P15 FINISHED
Object Bura language E788834 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: Bura language | Statement: [Bura people, language, Bura language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bura language
Context triple: [Bura people, language, Bura language]
  • A. Bura language chosen
    Bura language is a Chadic language spoken primarily in northeastern Nigeria by the Bura people.
  • B. Buru languages
    Buru languages are a small group of closely related Austronesian languages spoken primarily on Buru Island in Indonesia’s Maluku region.
  • C. Bura-Pabir language
    The Bura-Pabir language is a Chadic language spoken primarily in northeastern Nigeria by the Bura and Pabir ethnic groups.
  • D. Bafia language
    The Bafia language is a Bantu language spoken primarily by the Bafia people in central Cameroon.
  • E. 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.
  • 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_69d85cd53a7c819080f5b9042c4c199e completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03fb0aee081909db1c54349ec8492 completed April 16, 2026, 1:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3665769c8190be1af51a82a5e75f completed May 9, 2026, 1:28 p.m.
Created at: April 10, 2026, 3:53 a.m.