Triple

T13513295
Position Surface form Disambiguated ID Type / Status
Subject 中国人民解放军建军节 E322691 entity
Predicate 相关城市 P25162 FINISHED
Object 南昌市 E66806 NE FINISHED

How this triple was built (3 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: 南昌市 | Statement: [中国人民解放军建军节, 相关城市, 南昌市]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 南昌市
Context triple: [中国人民解放军建军节, 相关城市, 南昌市]
  • A. 新余市
    新余市 is a county-level city in central Jiangxi Province, China, known for its steel industry and rapid industrial development.
  • B. 上饶市
    上饶市是位于中国江西省东北部的一座地级市，以其丰富的红色革命历史和武夷山、三清山等自然风光而闻名。
  • C. Nanchang chosen
    Nanchang is the capital and largest city of Jiangxi Province in southeastern China, known as an important regional industrial and transportation hub.
  • D. Fuzhou (Jiangxi)
    Fuzhou (Jiangxi) is a county-level city in eastern China that serves as an administrative and economic center within Jiangxi Province.
  • E. Nanchang municipal government
    Nanchang municipal government is the local governing authority of Nanchang, the capital city of Jiangxi Province in China, responsible for administering public affairs, urban development, and cultural heritage management.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: 相关城市
Context triple: [中国人民解放军建军节, 相关城市, 南昌市]
  • A. linkedCity
    Indicates that two entities are associated with each other through a specific city, such as being located in, connected via, or related by that city.
  • B. gatheredCities
    Indicates that one entity collected or assembled multiple cities together, typically into a group, list, or shared context.
  • C. associatedCityCode
    Indicates that an entity is linked or related to a specific city identified by its code.
  • D. hasAssociatedCity chosen
    Indicates that one entity is linked or related to a specific city, typically as its location, base, or primary area of association.
  • E. city2
    Indicates a relationship where one entity is identified as a city associated with, located in, or otherwise linked to another entity.
  • F. None of above.

Provenance (4 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_69d80766a21881909f21a1b7421d3b8a completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaf87ca288190a147fbdb2f90985f completed April 12, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75492676c81909602745e2b6436cb completed May 3, 2026, 1:58 p.m.
PD Predicate disambiguation batch_69dbae0b63748190b5e207f84b2532ea completed April 12, 2026, 2:36 p.m.
Created at: April 9, 2026, 9:44 p.m.