Triple

T18066355
Position Surface form Disambiguated ID Type / Status
Subject Yuki–Wappo E432303 entity
Predicate hasPart P35 FINISHED
Object Yuki 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: Yuki language | Statement: [Yuki–Wappo, hasPart, Yuki language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yuki language
Context triple: [Yuki–Wappo, hasPart, Yuki language]
  • A. Yuki language chosen
    The Yuki language is an endangered Native American language of Northern California traditionally spoken by the Yuki people, notable for its unique numeral system and complex phonology.
  • B. Kawaiisu language
    Kawaiisu language is an endangered Uto-Aztecan language traditionally spoken by the Kawaiisu people of southern California.
  • C. Kurichiya language
    Kurichiya language is a lesser-known Dravidian language spoken by the Kurichiya tribal community in the Indian state of Kerala.
  • D. Mikasuki language
    The Mikasuki language is a Native American Muskogean language traditionally spoken by the Miccosukee and Seminole peoples of Florida.
  • E. Keiyo language
    The Keiyo language is a Southern Nilotic language spoken by the Keiyo people of Kenya’s Rift Valley, closely associated with and linguistically similar to other Kalenjin languages such as Kipsigis.
  • 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_69d8b9070cac81909fa9473fb1c3f1c7 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4cce97ce08190a2f8762ce545e091 completed April 19, 2026, 12:39 p.m.
Created at: April 10, 2026, 10:26 a.m.