Triple

T4256742
Position Surface form Disambiguated ID Type / Status
Subject Northern Qi dynasty E95991 entity
Predicate hasEraName P2938 FINISHED
Object Wuping
Wuping was an era name used during the Northern Qi dynasty in imperial China, marking a specific reign period within that dynasty’s rule.
 E426970 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: Wuping | Statement: [Northern Qi dynasty, hasEraName, Wuping]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Wuping
Context triple: [Northern Qi dynasty, hasEraName, Wuping]
  • A. Yongcong
    Yongcong was a Qing dynasty imperial prince, one of the sons of the Qianlong Emperor of China.
  • B. Chuping
    Chuping is a town in the Malaysian state of Perlis, known for its extensive sugarcane plantations and hot climate.
  • C. Pizhou
    Pizhou is a county-level city administered by Xuzhou in Jiangsu Province, eastern China, known for its historical sites and regional commerce.
  • D. Wuyuan
    Wuyuan is a historic county in northeastern Jiangxi, China, famed for its well-preserved Huizhou-style architecture and picturesque rural landscapes.
  • E. Huangcun
    Huangcun is a town in Beijing, China, that serves as the administrative and commercial center of the city's southern Daxing District.
  • 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: Wuping
Triple: [Northern Qi dynasty, hasEraName, Wuping]
Generated description
Wuping was an era name used during the Northern Qi dynasty in imperial China, marking a specific reign period within that dynasty’s rule.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Wuping
Target entity description: Wuping was an era name used during the Northern Qi dynasty in imperial China, marking a specific reign period within that dynasty’s rule.
  • A. Yongcong
    Yongcong was a Qing dynasty imperial prince, one of the sons of the Qianlong Emperor of China.
  • B. Chuping
    Chuping is a town in the Malaysian state of Perlis, known for its extensive sugarcane plantations and hot climate.
  • C. Pizhou
    Pizhou is a county-level city administered by Xuzhou in Jiangsu Province, eastern China, known for its historical sites and regional commerce.
  • D. Wuyuan
    Wuyuan is a historic county in northeastern Jiangxi, China, famed for its well-preserved Huizhou-style architecture and picturesque rural landscapes.
  • E. Huangcun
    Huangcun is a town in Beijing, China, that serves as the administrative and commercial center of the city's southern Daxing District.
  • 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_69b3454095ac81909c2494f7ff294af1 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34ec321008190b2cc1aca6ab690c4 completed March 12, 2026, 11:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b78422a88190a67921ee38638ac8 completed March 14, 2026, 7:31 p.m.
NEDg Description generation batch_69b5bb4d7b8c8190910525c855c83b83 completed March 14, 2026, 7:47 p.m.
NED2 Entity disambiguation (via description) batch_69b5bbba644881908f2f3be9dda7042b completed March 14, 2026, 7:49 p.m.
Created at: March 12, 2026, 11:06 p.m.