Triple

T15496534
Position Surface form Disambiguated ID Type / Status
Subject Changshu E378831 entity
Predicate hasChineseName P4878 FINISHED
Object 常熟市
常熟市 is a county-level city in Jiangsu Province, China, known for its developed manufacturing industry, historical sites, and location within the Yangtze River Delta economic region.
 E1160440 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: 常熟市 | Statement: [Changshu, hasChineseName, 常熟市]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 常熟市
Context triple: [Changshu, hasChineseName, 常熟市]
  • A. 泰州
    泰州是中国江苏省中部的一座历史文化名城和重要港口城市，以长江水运、制造业和传统美食而闻名。
  • B. 宿迁市
    宿迁市 is a prefecture-level city in northern Jiangsu Province, China, known for its historical connection to the Huai River region and rapid modern development.
  • C. 松江市
    松江市 is the capital city of Shimane Prefecture in Japan, known for its historic Matsue Castle, scenic lakes, and traditional cultural atmosphere.
  • D. 溧阳
    溧阳 is a county-level city in Jiangsu Province, China, known for its scenic Tianmu Lake area and tea production.
  • E. Suzhou New District
    Suzhou New District is a major high-tech industrial and development zone in Suzhou, China, known for its advanced manufacturing, technology enterprises, and modern infrastructure.
  • 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: 常熟市
Triple: [Changshu, hasChineseName, 常熟市]
Generated description
常熟市 is a county-level city in Jiangsu Province, China, known for its developed manufacturing industry, historical sites, and location within the Yangtze River Delta economic region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 常熟市
Target entity description: 常熟市 is a county-level city in Jiangsu Province, China, known for its developed manufacturing industry, historical sites, and location within the Yangtze River Delta economic region.
  • A. 泰州
    泰州是中国江苏省中部的一座历史文化名城和重要港口城市，以长江水运、制造业和传统美食而闻名。
  • B. 宿迁市
    宿迁市 is a prefecture-level city in northern Jiangsu Province, China, known for its historical connection to the Huai River region and rapid modern development.
  • C. 松江市
    松江市 is the capital city of Shimane Prefecture in Japan, known for its historic Matsue Castle, scenic lakes, and traditional cultural atmosphere.
  • D. 溧阳
    溧阳 is a county-level city in Jiangsu Province, China, known for its scenic Tianmu Lake area and tea production.
  • E. Suzhou New District
    Suzhou New District is a major high-tech industrial and development zone in Suzhou, China, known for its advanced manufacturing, technology enterprises, and modern infrastructure.
  • 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_69d85cd53a7c819080f5b9042c4c199e completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03faecd60819091eeaa56c9c8f67d completed April 16, 2026, 1:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3665769c8190be1af51a82a5e75f completed May 9, 2026, 1:28 p.m.
NEDg Description generation batch_69ff37ac082c81908e057c2d61a79cf0 completed May 9, 2026, 1:33 p.m.
NED2 Entity disambiguation (via description) batch_69ff384962f88190964fc040a2a44aa8 completed May 9, 2026, 1:36 p.m.
Created at: April 10, 2026, 3:52 a.m.