Triple

T14305532
Position Surface form Disambiguated ID Type / Status
Subject Jinhua E354684 entity
Predicate hasCitySeat P15001 FINISHED
Object Wucheng District
Wucheng District is the central urban district and administrative seat of the prefecture-level city of Jinhua in Zhejiang Province, China.
E1166737 NE FINISHED

How this triple was built (4 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: Wucheng District | Statement: [Jinhua, hasCitySeat, Wucheng District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wucheng District
Context triple: [Jinhua, hasCitySeat, Wucheng District]
  • A. Yicheng District
    Yicheng District is an urban administrative district under the jurisdiction of Zaozhuang City in Shandong Province, eastern China.
  • B. Licheng District
    Licheng District is a central urban district of Quanzhou in Fujian Province, China, known for its historic architecture and cultural heritage.
  • C. Shuocheng District
    Shuocheng District is the central urban district and administrative heart of Shuozhou City in Shanxi Province, China.
  • D. Jianhua District
    Jianhua District is a central urban district of Qiqihar City in Heilongjiang Province, northeastern China.
  • E. Jinyuan District
    Jinyuan District is an urban administrative district of Taiyuan, the capital city of Shanxi Province in northern China.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Wucheng District
Triple: [Jinhua, hasCitySeat, Wucheng District]
Generated description
Wucheng District is the central urban district and administrative seat of the prefecture-level city of Jinhua in Zhejiang Province, China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Wucheng District
Target entity description: Wucheng District is the central urban district and administrative seat of the prefecture-level city of Jinhua in Zhejiang Province, China.
  • A. Yicheng District
    Yicheng District is an urban administrative district under the jurisdiction of Zaozhuang City in Shandong Province, eastern China.
  • B. Licheng District
    Licheng District is a central urban district of Quanzhou in Fujian Province, China, known for its historic architecture and cultural heritage.
  • C. Shuocheng District
    Shuocheng District is the central urban district and administrative heart of Shuozhou City in Shanxi Province, China.
  • D. Jianhua District
    Jianhua District is a central urban district of Qiqihar City in Heilongjiang Province, northeastern China.
  • E. Jinyuan District
    Jinyuan District is an urban administrative district of Taiyuan, the capital city of Shanxi Province in northern China.
  • F. None of above. chosen

Provenance (5 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_69d8278ed42c8190b9f882dcce611347 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de85afabe48190926d6098047f4bcf completed April 14, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff56afa5ec8190a058574dff7431dc completed May 9, 2026, 3:45 p.m.
NEDg Description generation batch_69ff57c304188190afa695ae88cf0234 completed May 9, 2026, 3:50 p.m.
NED2 Entity disambiguation (via description) batch_69ff5920436c81909addad5bb4566ae9 completed May 9, 2026, 3:56 p.m.
Created at: April 10, 2026, 1:12 a.m.