Triple

T9161514
Position Surface form Disambiguated ID Type / Status
Subject Jiangmen E219834 entity
Predicate administers P123 FINISHED
Object Enping City E541866 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: Enping City | Statement: [Jiangmen, administers, Enping City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Enping City
Context triple: [Jiangmen, administers, Enping City]
  • A. Enping chosen
    Enping is a county-level city in Guangdong Province, China, known as part of the Sze Yup region and for its significant overseas Chinese diaspora.
  • B. Wanning
    Wanning is a county-level coastal city in southeastern Hainan, China, known for its tropical climate, beaches, and surf-friendly bays.
  • C. Huanghua Town
    Huanghua Town is a township-level division in the Changsha area of Hunan Province, China, known primarily for encompassing the vicinity of Changsha Huanghua International Airport.
  • D. Haining
    Haining is a county-level city in Zhejiang Province, China, known for its dramatic tidal bore on the Qiantang River and its textile industry.
  • E. Haozhou
    Haozhou is a historical city in China, known as the birthplace of the Hongwu Emperor, founder of the Ming dynasty.
  • 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_69ca83e3633c81908688a9fa2306ba99 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccaa2ac0508190b2f5c801c2c26d66 completed April 1, 2026, 5:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0547073cc8190999fe640c7ccd373 completed April 3, 2026, 11:59 p.m.
Created at: March 30, 2026, 7:21 p.m.