Triple

T18588380
Position Surface form Disambiguated ID Type / Status
Subject Leizhou Min E454296 entity
Predicate spokenIn P2266 FINISHED
Object Zhanjiang area NE NERFINISHED

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: Zhanjiang area | Statement: [Leizhou Min, spokenIn, Zhanjiang area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zhanjiang area
Context triple: [Leizhou Min, spokenIn, Zhanjiang area]
  • A. Zhanjiang chosen
    Zhanjiang is a coastal city in southwestern Guangdong, China, known for its important port, maritime industries, and strategic location on the Leizhou Peninsula.
  • B. Jiangmen
    Jiangmen is a coastal prefecture-level city in Guangdong Province, China, known as part of the Pearl River Delta economic region and historically as a major source of overseas Chinese emigration.
  • C. Huangsha area
    The Huangsha area is a commercial and transportation hub in Guangzhou, China, known for its markets, riverfront location, and connectivity via the metro system.
  • D. Nanhai
    Nanhai is an alternative name for Nanhai Lake, a notable body of water often associated with scenic and cultural significance in its region.
  • E. Maoming
    Maoming is a coastal city in southwestern Guangdong, China, known for its petrochemical industry and agricultural production, especially lychees and longans.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d38ae7e081908a98df1251842402 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e545b3e564819088e60fc25d1976f0 completed April 19, 2026, 9:14 p.m.
Created at: April 10, 2026, 11:44 a.m.