Triple

T2708614
Position Surface form Disambiguated ID Type / Status
Subject Xuzhou E59803 entity
Predicate hasSubdivision P747 FINISHED
Object Pizhou
Pizhou is a county-level city administered by Xuzhou in Jiangsu Province, eastern China, known for its historical sites and regional commerce.
 E290942 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: Pizhou | Statement: [Xuzhou, hasSubdivision, Pizhou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Pizhou
Context triple: [Xuzhou, hasSubdivision, Pizhou]
  • A. Yangsansi
    Yangsansi is a city in South Korea located within Gyeonggi Province, forming part of the greater Seoul metropolitan area.
  • B. Xishan
    Xishan is the given name of Yan Xishan, a prominent Chinese warlord and political leader active in Shanxi during the early 20th century.
  • C. Xijing
    Xijing is the historical name of Xi'an, one of China’s oldest and most important ancient capitals.
  • D. Zijincheng
    Zijincheng is the Chinese name for the Forbidden City, the vast imperial palace complex in central Beijing that served as the home of emperors and the political heart of China for nearly five centuries.
  • E. Diqing
    Diqing is an autonomous prefecture in northwestern Yunnan Province, China, known for its Tibetan culture, high-altitude landscapes, and proximity to the eastern Himalayas.
  • 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: Pizhou
Triple: [Xuzhou, hasSubdivision, Pizhou]
Generated description
Pizhou is a county-level city administered by Xuzhou in Jiangsu Province, eastern China, known for its historical sites and regional commerce.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Pizhou
Target entity description: Pizhou is a county-level city administered by Xuzhou in Jiangsu Province, eastern China, known for its historical sites and regional commerce.
  • A. Yangsansi
    Yangsansi is a city in South Korea located within Gyeonggi Province, forming part of the greater Seoul metropolitan area.
  • B. Xishan
    Xishan is the given name of Yan Xishan, a prominent Chinese warlord and political leader active in Shanxi during the early 20th century.
  • C. Xijing
    Xijing is the historical name of Xi'an, one of China’s oldest and most important ancient capitals.
  • D. Zijincheng
    Zijincheng is the Chinese name for the Forbidden City, the vast imperial palace complex in central Beijing that served as the home of emperors and the political heart of China for nearly five centuries.
  • E. Diqing
    Diqing is an autonomous prefecture in northwestern Yunnan Province, China, known for its Tibetan culture, high-altitude landscapes, and proximity to the eastern Himalayas.
  • 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_69ab4ac92a088190bc74bca14038e3de completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abda7542548190bbf6c947145f7f63 completed March 7, 2026, 7:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69afaf7f99508190acfd00baec64b7e9 completed March 10, 2026, 5:43 a.m.
NEDg Description generation batch_69afb02d8ff08190af2224c03b762c68 completed March 10, 2026, 5:46 a.m.
NED2 Entity disambiguation (via description) batch_69afb0ae71888190ab0675b7897f1589 completed March 10, 2026, 5:48 a.m.
Created at: March 6, 2026, 9:55 p.m.