Triple

T7946625
Position Surface form Disambiguated ID Type / Status
Subject Xiong clan E184513 entity
Predicate claimedAncestryFrom P30356 FINISHED
Object Gaoyang
Gaoyang is a legendary figure in ancient Chinese mythology, often associated with early royal lineages and revered as an ancestral progenitor by various clans.
 E704511 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: Gaoyang | Statement: [Xiong clan, claimedAncestryFrom, Gaoyang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gaoyang
Context triple: [Xiong clan, claimedAncestryFrom, Gaoyang]
  • A. Zhaoyuan
    Zhaoyuan is a county-level city in eastern China's Shandong province, known for its rich gold mining industry and economic development.
  • B. Hengshui
    Hengshui is a prefecture-level city in southeastern Hebei Province, China, known for its traditional culture, agriculture, and growing industrial base.
  • C. 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.
  • D. Yongcheng
    Yongcheng was a Qing dynasty imperial prince, known as one of the sons of the Qianlong Emperor of China.
  • E. Lingang
    Lingang is a rapidly developing industrial and high-tech district in Shanghai, China, known for hosting major manufacturing facilities such as Tesla’s Gigafactory Shanghai.
  • 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: Gaoyang
Triple: [Xiong clan, claimedAncestryFrom, Gaoyang]
Generated description
Gaoyang is a legendary figure in ancient Chinese mythology, often associated with early royal lineages and revered as an ancestral progenitor by various clans.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gaoyang
Target entity description: Gaoyang is a legendary figure in ancient Chinese mythology, often associated with early royal lineages and revered as an ancestral progenitor by various clans.
  • A. Zhaoyuan
    Zhaoyuan is a county-level city in eastern China's Shandong province, known for its rich gold mining industry and economic development.
  • B. Hengshui
    Hengshui is a prefecture-level city in southeastern Hebei Province, China, known for its traditional culture, agriculture, and growing industrial base.
  • C. 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.
  • D. Yongcheng
    Yongcheng was a Qing dynasty imperial prince, known as one of the sons of the Qianlong Emperor of China.
  • E. Lingang
    Lingang is a rapidly developing industrial and high-tech district in Shanghai, China, known for hosting major manufacturing facilities such as Tesla’s Gigafactory Shanghai.
  • 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_69ca8291c2008190b1b8832c87814bcf completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3b29a570819091a2ac185a8d57c4 completed March 31, 2026, 3:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe02faa308190aeba83cc6cb96153 completed March 31, 2026, 2:54 p.m.
NEDg Description generation batch_69cbe4383d0c819085e7c95e7b0be16e completed March 31, 2026, 3:11 p.m.
NED2 Entity disambiguation (via description) batch_69cc34a83cec81908aba7afbaea53449 completed March 31, 2026, 8:55 p.m.
Created at: March 30, 2026, 5:09 p.m.