Triple

T1846087
Position Surface form Disambiguated ID Type / Status
Subject Hu Jintao E41285 entity
Predicate bornIn P1 FINISHED
Object Taizhou
Taizhou is a city in eastern China known as the birthplace of former Chinese president Hu Jintao.
 E143408 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: Taizhou | Statement: [Hu Jintao, bornIn, Taizhou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Taizhou
Context triple: [Hu Jintao, bornIn, Taizhou]
  • A. Taizhou
    Taizhou is a prefecture-level city in eastern China known for its historical heritage and location along the Yangtze River in Jiangsu province.
  • B. Wenzhou
    Wenzhou is a major coastal city in southeastern Zhejiang Province, China, known for its entrepreneurial culture, export-driven economy, and large overseas Chinese community.
  • C. Zhenjiang
    Zhenjiang is a historic port city in eastern China known for its strategic location on the Yangtze River and its rich cultural and culinary heritage.
  • D. Nantong
    Nantong is a coastal city in eastern China known for its textile industry, river and sea ports, and location on the northern bank of the Yangtze River opposite Shanghai.
  • E. 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.
  • 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: Taizhou
Triple: [Hu Jintao, bornIn, Taizhou]
Generated description
Taizhou is a city in eastern China known as the birthplace of former Chinese president Hu Jintao.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Taizhou
Target entity description: Taizhou is a city in eastern China known as the birthplace of former Chinese president Hu Jintao.
  • A. Taizhou chosen
    Taizhou is a prefecture-level city in eastern China known for its historical heritage and location along the Yangtze River in Jiangsu province.
  • B. Wenzhou
    Wenzhou is a major coastal city in southeastern Zhejiang Province, China, known for its entrepreneurial culture, export-driven economy, and large overseas Chinese community.
  • C. Zhenjiang
    Zhenjiang is a historic port city in eastern China known for its strategic location on the Yangtze River and its rich cultural and culinary heritage.
  • D. Nantong
    Nantong is a coastal city in eastern China known for its textile industry, river and sea ports, and location on the northern bank of the Yangtze River opposite Shanghai.
  • E. 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.
  • F. None of above.

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_69a88648cd44819093303206d96d76ad completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb051640c819088a8b28a03f57331 completed March 7, 2026, 4:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae95e5cf008190a6638bb2c8d4d505 completed March 9, 2026, 9:41 a.m.
NEDg Description generation batch_69ae9694c390819095b3e935224902d3 completed March 9, 2026, 9:44 a.m.
NED2 Entity disambiguation (via description) batch_69ae9a5b2a04819091b102c51a5b2af4 completed March 9, 2026, 10 a.m.
Created at: March 4, 2026, 7:33 p.m.