Triple

T22849579
Position Surface form Disambiguated ID Type / Status
Subject Kachin language E566320 entity
Predicate closelyRelatedTo P37 FINISHED
Object Zaiwa language NE NERFINISHED

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: Zaiwa language | Statement: [Kachin language, closelyRelatedTo, Zaiwa language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zaiwa language
Context triple: [Kachin language, closelyRelatedTo, Zaiwa language]
  • A. Zaiwa language chosen
    The Zaiwa language is a Tibeto-Burman language spoken primarily by the Zaiwa people in parts of Yunnan, China and northern Myanmar.
  • B. Wauja language
    The Wauja language is an indigenous Arawakan language spoken by the Wauja people of Brazil’s Upper Xingu region in the Amazon.
  • C. Zigua language
    The Zigua language is a Bantu language spoken primarily in northeastern Tanzania by the Zigua people.
  • D. Sayawa language
    The Sayawa language is a Chadic language spoken primarily by the Sayawa people in Bauchi State, northeastern Nigeria.
  • E. Zezuru language
    The Zezuru language is a major dialect of Shona spoken primarily in central and northern Zimbabwe.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e2458750b481908a8e4cf4609cc6cf completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17eb74700819090d191b3a7a17034 completed April 29, 2026, 3:44 a.m.
Created at: April 17, 2026, 3:36 p.m.