Triple

T1654803
Position Surface form Disambiguated ID Type / Status
Subject Jiangxi Province E35773 entity
Predicate hasCity P316 FINISHED
Object Xinyu
Xinyu is a prefecture-level industrial city located in central Jiangxi Province in southeastern China.
E187720 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: Xinyu | Statement: [Jiangxi Province, hasCity, Xinyu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Xinyu
Context triple: [Jiangxi Province, hasCity, Xinyu]
  • A. Xiantao
    Xiantao is a county-level city in central China’s Hubei province, known for its location on the Jianghan Plain and its role as a regional agricultural and industrial center.
  • B. Zhizhong
    Zhizhong is a Chinese given name shared by various individuals, including historical and contemporary figures.
  • C. Luyang
    Luyang is a historic name associated with the city of Hefei, the capital of Anhui Province in eastern China.
  • D. Kaihui
    Kaihui is a Chinese given name most notably borne by Yang Kaihui, the revolutionary and early partner of Mao Zedong.
  • E. Xianning
    Xianning is a prefecture-level city in southeastern Hubei Province, China, known for its hot springs, karst landscapes, and historical sites.
  • 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: Xinyu
Triple: [Jiangxi Province, hasCity, Xinyu]
Generated description
Xinyu is a prefecture-level industrial city located in central Jiangxi Province in southeastern China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Xinyu
Target entity description: Xinyu is a prefecture-level industrial city located in central Jiangxi Province in southeastern China.
  • A. Xiantao
    Xiantao is a county-level city in central China’s Hubei province, known for its location on the Jianghan Plain and its role as a regional agricultural and industrial center.
  • B. Zhizhong
    Zhizhong is a Chinese given name shared by various individuals, including historical and contemporary figures.
  • C. Luyang
    Luyang is a historic name associated with the city of Hefei, the capital of Anhui Province in eastern China.
  • D. Kaihui
    Kaihui is a Chinese given name most notably borne by Yang Kaihui, the revolutionary and early partner of Mao Zedong.
  • E. Xianning
    Xianning is a prefecture-level city in southeastern Hubei Province, China, known for its hot springs, karst landscapes, and historical sites.
  • 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_69a8860568888190a32cd9f70acbba42 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90a8b597c81908a62b41718d85df6 completed March 5, 2026, 4:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad6821d18c8190b411bb031c142580 completed March 8, 2026, 12:14 p.m.
NEDg Description generation batch_69ad68a9769081908a0748b8d02b8379 completed March 8, 2026, 12:16 p.m.
NED2 Entity disambiguation (via description) batch_69ad692d61288190ad0c0265f49643ac completed March 8, 2026, 12:18 p.m.
Created at: March 4, 2026, 7:29 p.m.