Triple

T22431905
Position Surface form Disambiguated ID Type / Status
Subject Gao-Yang Yue E554519 entity
Predicate spokenIn P2266 FINISHED
Object Guangdong province 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: Guangdong province | Statement: [Gao-Yang Yue, spokenIn, Guangdong province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guangdong province
Context triple: [Gao-Yang Yue, spokenIn, Guangdong province]
  • A. Guangdong Province chosen
    Guangdong Province is a populous and economically vital coastal region in southern China, known for major cities like Guangzhou and Shenzhen and its role as a manufacturing and trade hub.
  • B. Zhejiang Province
    Zhejiang Province is a coastal province in eastern China known for its dynamic private-sector economy, major port cities like Ningbo, and scenic areas such as Hangzhou and the West Lake.
  • C. Jiaozhi Province
    Jiaozhi Province was a Ming dynasty colonial administrative region established in northern Vietnam during the early 15th century.
  • D. Lau Province
    Lau Province is a remote island province of Fiji comprising the Lau Islands in the country’s eastern maritime region.
  • 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 (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_69e11e5010e48190ae1e9c9db9697637 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15a32139481909baaf9275f5e0257 completed April 29, 2026, 1:09 a.m.
Created at: April 16, 2026, 8:47 p.m.