Triple

T18181985
Position Surface form Disambiguated ID Type / Status
Subject Qinzhou E435308 entity
Predicate locatedNear P294 FINISHED
Object Fangchenggang 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: Fangchenggang | Statement: [Qinzhou, locatedNear, Fangchenggang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fangchenggang
Context triple: [Qinzhou, locatedNear, Fangchenggang]
  • A. Fangchenggang chosen
    Fangchenggang is a coastal prefecture-level city in southern China known for its port on the Gulf of Tonkin and proximity to the Vietnam border.
  • B. Lianyungang
    Lianyungang is a major coastal city and seaport in eastern China, serving as an important transportation and trade hub on the Yellow Sea.
  • C. Longkou
    Longkou is a coastal city in northeastern Shandong Province, China, known for its port, marine-based industries, and production of Longkou vermicelli.
  • D. Dongyang
    Dongyang is a county-level city in central Zhejiang Province, China, known for its woodcarving tradition and as part of the Jinhua metropolitan area.
  • E. Kaiping
    Kaiping is a county-level city in Guangdong Province, China, known for its distinctive diaolou watchtowers and as part of the Sze Yup region with a strong overseas Chinese heritage.
  • 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_69d8b90c7ec081909b4694ccecb449c6 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4dffb3bc88190a627be9c444d5c7d completed April 19, 2026, 2 p.m.
Created at: April 10, 2026, 10:31 a.m.