Triple

T1629357
Position Surface form Disambiguated ID Type / Status
Subject Lingnan E35222 entity
Predicate hasPart P35 FINISHED
Object Guangxi E99799 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: Guangxi | Statement: [Lingnan, hasPart, Guangxi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guangxi
Context triple: [Lingnan, hasPart, Guangxi]
  • A. Guangxi Province chosen
    Guangxi Province is an autonomous region in southern China known for its ethnically diverse population, karst landscapes, and strategic location bordering Vietnam.
  • B. 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.
  • C. Guizhou Province
    Guizhou Province is a mountainous, ethnically diverse region in southwest China known for its karst landscapes, cool climate, and rapid economic development.
  • D. 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.
  • E. Fujian
    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.
  • 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_69a886036bc081909ff5de16dbe5e8ea completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a909f257948190b3398fd6dc91f586 completed March 5, 2026, 4:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad79813b2c819093bf3833db398f22 completed March 8, 2026, 1:28 p.m.
Created at: March 4, 2026, 7:28 p.m.