Triple

T16935009
Position Surface form Disambiguated ID Type / Status
Subject Hokkien E410805 entity
Predicate spokenIn P2266 FINISHED
Object Fujian E41238 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: Fujian | Statement: [Hokkien, spokenIn, Fujian]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fujian
Context triple: [Hokkien, spokenIn, Fujian]
  • A. Fujian chosen
    Fujian is a coastal province in southeastern China known for its significant role in Chinese migration, distinctive Min culture and dialects, and historic maritime trade.
  • B. Jianxi
    Jianxi was an era name used during the reign of Emperor Ling of the Eastern Han dynasty in ancient China.
  • C. Inland Fujian
    Inland Fujian is the mountainous, landlocked interior region of China’s Fujian province, characterized by forested hills, river valleys, and relatively less coastal development.
  • D. Kansu
    Kansu is a Turkish surname most notably associated with Şevket Aziz Kansu, a prominent Turkish academic and anthropologist.
  • E. Guangdong Province
    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.
  • 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_69d886c886688190967be07322597ac9 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3cf2899608190a6bacdce9d4ceb84 completed April 18, 2026, 6:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00cfe2d4f48190b965b6c0a3cc0125 completed May 10, 2026, 6:35 p.m.
Created at: April 10, 2026, 5:30 a.m.