Triple

T12151124
Position Surface form Disambiguated ID Type / Status
Subject Myene people E289454 entity
Predicate usesLanguage P238 FINISHED
Object Myene language E908747 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: Myene language | Statement: [Myene people, usesLanguage, Myene language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Myene language
Context triple: [Myene people, usesLanguage, Myene language]
  • A. Myene language chosen
    The Myene language is a Bantu language spoken primarily along the coast of Gabon by the Myene people.
  • B. Minyag language
    The Minyag language is a lesser-known Qiangic language spoken by the Minyag people in parts of western Sichuan, China.
  • C. Muinane language
    The Muinane language is an indigenous Witotoan language spoken by the Muinane people of the Colombian Amazon.
  • D. Semai language
    The Semai language is an Austroasiatic language spoken by the Semai people, an indigenous Orang Asli group in Peninsular Malaysia.
  • E. Mehináku language
    The Mehináku language is an indigenous Arawakan language spoken by the Mehinaku people of Brazil’s Upper Xingu region in the Amazon.
  • 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_69d6ab4c6710819097a9d228382dde43 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915ae736c8190aaab05efb93c5854 completed April 10, 2026, 3:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60a80aa6881908111cc47b5fe8b9e completed May 2, 2026, 2:30 p.m.
Created at: April 8, 2026, 9:49 p.m.