Triple

T22542963
Position Surface form Disambiguated ID Type / Status
Subject Nanning railway station E557341 entity
Predicate connectsTo P845 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: [Nanning railway station, connectsTo, Fangchenggang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fangchenggang
Context triple: [Nanning railway station, connectsTo, 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_69e11e58662081909ae346ab384514ca completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15f330a40819098df6a9b0f27635e completed April 29, 2026, 1:30 a.m.
Created at: April 16, 2026, 8:51 p.m.