Triple

T12074577
Position Surface form Disambiguated ID Type / Status
Subject Dong E287513 entity
Predicate primaryRegion P1103 FINISHED
Object Guizhou Province 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 Province | Statement: [Dong, primaryRegion, Guizhou Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guizhou Province
Context triple: [Dong, primaryRegion, Guizhou Province]
  • 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. Kansu
    Kansu is a Turkish surname most notably associated with Şevket Aziz Kansu, a prominent Turkish academic and anthropologist.
  • E. Bié Province
    Bié Province is a central Angolan province known for its highland terrain, agricultural activity, and strategic location bordering several other provinces.
  • 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_69d6ab4846e081908ee7bbd66a6d3459 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9045bbc508190abf6e3316701e587 completed April 10, 2026, 2:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62a7c2b0081909994ea88683a39f4 completed May 2, 2026, 4:46 p.m.
Created at: April 8, 2026, 9:48 p.m.