Triple

T8530857
Position Surface form Disambiguated ID Type / Status
Subject Later Zhou E201942 entity
Predicate eraName P2938 FINISHED
Object Guangshun
Guangshun was the brief final era name used by the Later Zhou dynasty in 10th-century China, marking the closing phase of that regime before the rise of the Song dynasty.
 E765520 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: Guangshun | Statement: [Later Zhou, eraName, Guangshun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Guangshun
Context triple: [Later Zhou, eraName, Guangshun]
  • A. Guangyuan
    Guangyuan is a prefecture-level city in northern Sichuan, China, known as a regional transport hub with historical and cultural significance along the upper reaches of the Jialing River.
  • B. Guanghe
    Guanghe was an era name used during the reign of Emperor Ling of the Eastern Han dynasty in ancient China.
  • C. Guanggu
    Guanggu is a major high-tech development zone in Wuhan, China, known as an innovation hub for the optics and electronics industries.
  • D. Yongcheng
    Yongcheng was a Qing dynasty imperial prince, known as one of the sons of the Qianlong Emperor of China.
  • E. Yuncheng
    Yuncheng is a major city in southern Shanxi Province, China, known for its historical sites and role as a regional transportation and economic hub.
  • 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: Guangshun
Triple: [Later Zhou, eraName, Guangshun]
Generated description
Guangshun was the brief final era name used by the Later Zhou dynasty in 10th-century China, marking the closing phase of that regime before the rise of the Song dynasty.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Guangshun
Target entity description: Guangshun was the brief final era name used by the Later Zhou dynasty in 10th-century China, marking the closing phase of that regime before the rise of the Song dynasty.
  • A. Guangyuan
    Guangyuan is a prefecture-level city in northern Sichuan, China, known as a regional transport hub with historical and cultural significance along the upper reaches of the Jialing River.
  • B. Guanghe
    Guanghe was an era name used during the reign of Emperor Ling of the Eastern Han dynasty in ancient China.
  • C. Guanggu
    Guanggu is a major high-tech development zone in Wuhan, China, known as an innovation hub for the optics and electronics industries.
  • D. Yongcheng
    Yongcheng was a Qing dynasty imperial prince, known as one of the sons of the Qianlong Emperor of China.
  • E. Yuncheng
    Yuncheng is a major city in southern Shanxi Province, China, known for its historical sites and role as a regional transportation and economic hub.
  • 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_69ca83228b24819085d22e7dc99f5d94 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe67546248190b359c845c0161ad3 completed March 31, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69cfb9f030fc8190961bcb067350e3e6 completed April 3, 2026, 1 p.m.
NEDg Description generation batch_69cfbacea9408190a38f14817437c382 completed April 3, 2026, 1:04 p.m.
NED2 Entity disambiguation (via description) batch_69cfbb6235148190850865a734d55a6c completed April 3, 2026, 1:06 p.m.
Created at: March 30, 2026, 6:17 p.m.