Triple

T2118809
Position Surface form Disambiguated ID Type / Status
Subject Cathaya E43868 entity
Predicate foundIn P40 FINISHED
Object Guizhou E57456 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: Guizhou | Statement: [Cathaya, foundIn, Guizhou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guizhou
Context triple: [Cathaya, foundIn, 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. Guangxi Province
    Guangxi Province is an autonomous region in southern China known for its ethnically diverse population, karst landscapes, and strategic location bordering Vietnam.
  • D. Sichuan Province
    Sichuan Province is a populous landlocked region in southwestern China known for its spicy cuisine, rich cultural heritage, and diverse mountainous landscapes including parts of the Tibetan Plateau.
  • E. Jiangxi Province
    Jiangxi Province is an inland province in southeastern China known for its rich revolutionary history, porcelain production in Jingdezhen, and scenic landscapes such as Lushan Mountain and Poyang Lake.
  • 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_69a88717cfe48190b7ecdd68c824848a completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abbb3117c081908c5e748a869d1f9f completed March 7, 2026, 5:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6aec3694819090d0e7cf02944aa3 completed March 9, 2026, 6:38 a.m.
Created at: March 4, 2026, 7:44 p.m.