Triple

T9688969
Position Surface form Disambiguated ID Type / Status
Subject Kannon E234489 entity
Predicate hasAlternativeSpelling P457 FINISHED
Object Kwan-non
Kwan-non is an alternative spelling of Kannon, the Japanese Buddhist bodhisattva of compassion derived from the Chinese Guanyin.
 E815572 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: Kwan-non | Statement: [Kannon, hasAlternativeSpelling, Kwan-non]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kwan-non
Context triple: [Kannon, hasAlternativeSpelling, Kwan-non]
  • A. Kwan
    Kwan is a Chinese-origin surname shared by many individuals, including the renowned American figure skater Michelle Kwan.
  • B. Kwang-chou
    Kwang-chou is an alternative romanization of Guangzhou, the major port city and economic hub in southern China historically known in the West as Canton.
  • C. Kook-Chun
    Kook-Chun is the family name of actor Shannon Kook, known for his roles in film and television.
  • D. Yukong
    Yukong was the former name of SK Energy, a major South Korean petroleum and energy company within the SK Group conglomerate.
  • E. Chi-Fu
    Chi-Fu is the pompous and bureaucratic imperial advisor in Disney's 1998 animated film "Mulan," often serving as a comedic antagonist to the protagonist's efforts.
  • 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: Kwan-non
Triple: [Kannon, hasAlternativeSpelling, Kwan-non]
Generated description
Kwan-non is an alternative spelling of Kannon, the Japanese Buddhist bodhisattva of compassion derived from the Chinese Guanyin.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kwan-non
Target entity description: Kwan-non is an alternative spelling of Kannon, the Japanese Buddhist bodhisattva of compassion derived from the Chinese Guanyin.
  • A. Kwan
    Kwan is a Chinese-origin surname shared by many individuals, including the renowned American figure skater Michelle Kwan.
  • B. Kwang-chou
    Kwang-chou is an alternative romanization of Guangzhou, the major port city and economic hub in southern China historically known in the West as Canton.
  • C. Kook-Chun
    Kook-Chun is the family name of actor Shannon Kook, known for his roles in film and television.
  • D. Yukong
    Yukong was the former name of SK Energy, a major South Korean petroleum and energy company within the SK Group conglomerate.
  • E. Chi-Fu
    Chi-Fu is the pompous and bureaucratic imperial advisor in Disney's 1998 animated film "Mulan," often serving as a comedic antagonist to the protagonist's efforts.
  • 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_69ca84ca73208190957a900c8543bdcc completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9d019d40819095059a4d6167900a completed April 1, 2026, 10:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1911427d48190855506ab61f8a2ce completed April 4, 2026, 10:30 p.m.
NEDg Description generation batch_69d193a5cdac8190b84564f397d00124 completed April 4, 2026, 10:41 p.m.
NED2 Entity disambiguation (via description) batch_69d19457c6488190a7bc72e1a27c088a completed April 4, 2026, 10:44 p.m.
Created at: March 30, 2026, 8:17 p.m.