Triple

T22569845
Position Surface form Disambiguated ID Type / Status
Subject Yi languages E558049 entity
Predicate spokenIn P2266 FINISHED
Object Guizhou 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: Guizhou | Statement: [Yi languages, spokenIn, Guizhou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guizhou
Context triple: [Yi languages, spokenIn, Guizhou]
  • A. Guizhou Province chosen
    Guizhou Province is a mountainous, ethnically diverse region in southwest China known for its karst landscapes, cool climate, and rapid economic development.
  • B. Yunnan Province
    Yunnan Province is a mountainous, ethnically diverse region in southwest China known for its rich biodiversity, tea culture, and border location with countries such as Myanmar, Laos, and Vietnam.
  • C. Kansu
    Kansu is a Turkish surname most notably associated with Şevket Aziz Kansu, a prominent Turkish academic and anthropologist.
  • D. Guangxi Province
    Guangxi Province is an autonomous region in southern China known for its ethnically diverse population, karst landscapes, and strategic location bordering Vietnam.
  • E. Rehe Province
    Rehe Province was a former northeastern Chinese province bordering Manchuria and Inner Mongolia that became a key battleground and occupation zone during Japan’s expansion in the 1930s.
  • 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_69e11e5ae4ac8190b1f503457603d969 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15fad35448190b51a3dd639ca8568 completed April 29, 2026, 1:32 a.m.
Created at: April 16, 2026, 8:52 p.m.