Triple

T12327144
Position Surface form Disambiguated ID Type / Status
Subject Nanping E293860 entity
Predicate bordersProvince P224 FINISHED
Object Jiangxi E35773 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: Jiangxi | Statement: [Nanping, bordersProvince, Jiangxi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jiangxi
Context triple: [Nanping, bordersProvince, Jiangxi]
  • A. Jiangxi Province chosen
    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.
  • B. Jianxi
    Jianxi was an era name used during the reign of Emperor Ling of the Eastern Han dynasty in ancient China.
  • C. Jiangsu
    Jiangsu is a populous and economically significant coastal province in eastern China, known for its rich history, dense urbanization, and major cities such as Nanjing and Suzhou.
  • D. Hubei Province
    Hubei Province is a landlocked region in central China known for its capital city Wuhan, major role in industry and transportation, and significant historical and cultural heritage.
  • E. Kansu
    Kansu is a Turkish surname most notably associated with Şevket Aziz Kansu, a prominent Turkish academic and anthropologist.
  • 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_69d6ab6ae0dc8190b1522a9c1c55c114 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f4f90a881908c5060dd197744d1 completed April 10, 2026, 6:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67c62e40481908a688912055c697c completed May 2, 2026, 10:36 p.m.
Created at: April 8, 2026, 9:53 p.m.