Triple

T6771454
Position Surface form Disambiguated ID Type / Status
Subject Sehwi language E155050 entity
Predicate neighboringLanguage P16383 FINISHED
Object Bono language E617319 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: Bono language | Statement: [Sehwi language, neighboringLanguage, Bono language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bono language
Context triple: [Sehwi language, neighboringLanguage, Bono language]
  • A. Bono language chosen
    The Bono language is a Central Tano (Akan) language of West Africa, spoken primarily by the Bono people of Ghana and closely related to other Akan varieties.
  • B. Bo language
    Bo language is an extinct Great Andamanese language once spoken by the Bo people of the Andaman Islands in India.
  • C. Bongo language
    The Bongo language is a Central Sudanic language spoken by the Bongo people of South Sudan.
  • D. Bonan language
    The Bonan language is an endangered Mongolic language spoken primarily by the Bonan ethnic group in Gansu and Qinghai provinces of China.
  • E. Bondei language
    The Bondei language is a Bantu language spoken by the Bondei people of northeastern Tanzania, particularly in the Tanga 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_69c68812ef7c819099369f51febb725c completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d2496fa08190895d8b625fb0d699 completed March 27, 2026, 6:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69c71a803fe08190b4dc32d09e91da07 completed March 28, 2026, 12:02 a.m.
Created at: March 27, 2026, 2:13 p.m.