Triple

T8006732
Position Surface form Disambiguated ID Type / Status
Subject King Huai of Chu E186380 entity
Predicate givenName P17 FINISHED
Object Xiong Huai
Xiong Huai was an ancient Chinese monarch who ruled the state of Chu during the Warring States period.
E752594 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: Xiong Huai | Statement: [King Huai of Chu, givenName, Xiong Huai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Xiong Huai
Context triple: [King Huai of Chu, givenName, Xiong Huai]
  • A. Xiong Lü
    Xiong Lü was the personal name of King Zhuang of Chu, a prominent and powerful monarch of the ancient Chinese state of Chu during the Spring and Autumn period.
  • B. Han Xianchu
    Han Xianchu was a prominent Chinese military commander of the People’s Liberation Army, known for his key roles in major campaigns during the Chinese Civil War and the Korean War.
  • C. Zhu Houxi
    Zhu Houxi was a Ming dynasty imperial prince, known primarily as a son of the Hongzhi Emperor of China.
  • D. Xun Kuang
    Xun Kuang, better known as Xunzi, was an influential Warring States–period Confucian philosopher noted for his belief in the innate badness of human nature and the importance of ritual and education.
  • E. Hui Xiong
    Hui Xiong is a prominent computer scientist and data mining researcher recognized for his influential contributions to knowledge discovery and data analytics.
  • 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: Xiong Huai
Triple: [King Huai of Chu, givenName, Xiong Huai]
Generated description
Xiong Huai was an ancient Chinese monarch who ruled the state of Chu during the Warring States period.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Xiong Huai
Target entity description: Xiong Huai was an ancient Chinese monarch who ruled the state of Chu during the Warring States period.
  • A. Xiong Lü
    Xiong Lü was the personal name of King Zhuang of Chu, a prominent and powerful monarch of the ancient Chinese state of Chu during the Spring and Autumn period.
  • B. Han Xianchu
    Han Xianchu was a prominent Chinese military commander of the People’s Liberation Army, known for his key roles in major campaigns during the Chinese Civil War and the Korean War.
  • C. Zhu Houxi
    Zhu Houxi was a Ming dynasty imperial prince, known primarily as a son of the Hongzhi Emperor of China.
  • D. Xun Kuang
    Xun Kuang, better known as Xunzi, was an influential Warring States–period Confucian philosopher noted for his belief in the innate badness of human nature and the importance of ritual and education.
  • E. Hui Xiong
    Hui Xiong is a prominent computer scientist and data mining researcher recognized for his influential contributions to knowledge discovery and data analytics.
  • 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_69ca82abaffc8190ab8af79cdbc31ab3 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3cf8a6048190970685a83fd2f59d completed March 31, 2026, 3:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69cf278d5abc8190a9330918486e464f completed April 3, 2026, 2:35 a.m.
NEDg Description generation batch_69cf2a6a91d48190aa7d45b0a010f261 completed April 3, 2026, 2:48 a.m.
NED2 Entity disambiguation (via description) batch_69cf2c0aace08190aca839c39e718c52 completed April 3, 2026, 2:55 a.m.
Created at: March 30, 2026, 5:18 p.m.