Triple

T8659053
Position Surface form Disambiguated ID Type / Status
Subject Xiamen–Shenzhen Railway E205499 entity
Predicate passesThroughCity P416 FINISHED
Object Raoping
Raoping is a coastal county in eastern Guangdong, China, known for its Teochew culture and strategic location along major transport routes.
 E758541 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: Raoping | Statement: [Xiamen–Shenzhen Railway, passesThroughCity, Raoping]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Raoping
Context triple: [Xiamen–Shenzhen Railway, passesThroughCity, Raoping]
  • A. Lincang
    Lincang is a prefecture-level city in southwestern China known for its tea production, diverse ethnic cultures, and location near the border with Myanmar.
  • B. Jianyang
    Jianyang is a county-level city in northern Fujian Province, China, known for its historical role in tea production and its location along the Min River.
  • C. Jinyang
    Jinyang is the historical name of the city now known as Taiyuan, a major urban and industrial center in northern China’s Shanxi province.
  • D. Guanghe
    Guanghe was an era name used during the reign of Emperor Ling of the Eastern Han dynasty in ancient China.
  • E. Suihua
    Suihua is a prefecture-level city in northeastern China known for its agricultural production and cold climate.
  • 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: Raoping
Triple: [Xiamen–Shenzhen Railway, passesThroughCity, Raoping]
Generated description
Raoping is a coastal county in eastern Guangdong, China, known for its Teochew culture and strategic location along major transport routes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Raoping
Target entity description: Raoping is a coastal county in eastern Guangdong, China, known for its Teochew culture and strategic location along major transport routes.
  • A. Lincang
    Lincang is a prefecture-level city in southwestern China known for its tea production, diverse ethnic cultures, and location near the border with Myanmar.
  • B. Jianyang
    Jianyang is a county-level city in northern Fujian Province, China, known for its historical role in tea production and its location along the Min River.
  • C. Jinyang
    Jinyang is the historical name of the city now known as Taiyuan, a major urban and industrial center in northern China’s Shanxi province.
  • D. Guanghe
    Guanghe was an era name used during the reign of Emperor Ling of the Eastern Han dynasty in ancient China.
  • E. Suihua
    Suihua is a prefecture-level city in northeastern China known for its agricultural production and cold climate.
  • 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_69ca8350897c819086cde7596fbe5fe7 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc486ece68819089c74bdf98b64490 completed March 31, 2026, 10:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf6ed1e0548190b02d43c5d7e65e08 completed April 3, 2026, 7:40 a.m.
NEDg Description generation batch_69cf7101b0088190843affad2474eb32 completed April 3, 2026, 7:49 a.m.
NED2 Entity disambiguation (via description) batch_69cf725ebb4c8190be3b19e9c5e854ac completed April 3, 2026, 7:55 a.m.
Created at: March 30, 2026, 6:30 p.m.