Triple

T6633030
Position Surface form Disambiguated ID Type / Status
Subject Shangdu E149972 entity
Predicate knownAs P39 FINISHED
Object Kaiping E551624 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: Kaiping | Statement: [Shangdu, knownAs, Kaiping]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kaiping
Context triple: [Shangdu, knownAs, Kaiping]
  • A. Kaiping chosen
    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.
  • B. Kaiping District
    Kaiping District is an urban district under the administration of Tangshan City in Hebei Province, China, known for its industrial base and coal-related industries.
  • C. Lianyungang
    Lianyungang is a major coastal city and seaport in eastern China, serving as an important transportation and trade hub on the Yellow Sea.
  • D. Huludao
    Huludao is a coastal city in southwestern Liaoning Province, China, known for its port, shipbuilding industry, and seaside tourism.
  • E. Panjin
    Panjin is an industrial and oil-producing city in northeastern China, best known for its striking Red Beach wetlands along the Bohai Sea.
  • 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_69c687ee50048190aa151765bef16193 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6afc9138c81909d228ce4936d6b8b completed March 27, 2026, 4:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cbf329f08190a3f29c4d4c6aa136 completed March 27, 2026, 6:26 p.m.
Created at: March 27, 2026, 1:59 p.m.