Triple

T22850218
Position Surface form Disambiguated ID Type / Status
Subject Qiangic group E566336 entity
Predicate hasPart P35 FINISHED
Object Namuyi 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: Namuyi language | Statement: [Qiangic group, hasPart, Namuyi language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Namuyi language
Context triple: [Qiangic group, hasPart, Namuyi language]
  • A. Namuyi language chosen
    The Namuyi language is a lesser-known Sino-Tibetan language spoken by the Namuyi people in parts of Sichuan and Yunnan in southwestern China.
  • B. Nyunga language
    The Nyunga language is an Australian Aboriginal language traditionally spoken by the Noongar people of southwestern Western Australia and is part of the broader Pama–Nyungan language family.
  • C. Murle language
    The Murle language is an Eastern Sudanic language spoken primarily by the Murle people of South Sudan.
  • D. Nyimang language
    Nyimang language is a Nilo-Saharan language spoken by the Nyimang people in the Nuba Mountains of Sudan.
  • E. Nyemba language
    The Nyemba language is a Bantu language spoken primarily by the Nyemba (Nyaneka-Nkhumbi) people of southwestern Angola.
  • 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.