Triple

T18572339
Position Surface form Disambiguated ID Type / Status
Subject Raffles Institution E453901 entity
Predicate hasAlumnus P51 FINISHED
Object Kuo Pao Kun
Kuo Pao Kun was a pioneering Singaporean playwright and theatre director widely regarded as a key figure in the development of contemporary theatre in Singapore.
 E1331357 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: Kuo Pao Kun | Statement: [Raffles Institution, hasAlumnus, Kuo Pao Kun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kuo Pao Kun
Context triple: [Raffles Institution, hasAlumnus, Kuo Pao Kun]
  • A. Chien-Po
    Chien-Po is a gentle, large, and good-natured warrior from Disney’s Mulan series, known for his calm demeanor and physical strength.
  • B. San Bao
    San Bao is a Chinese composer best known for his film scores and music for director Zhang Yimou’s movies.
  • C. Chao Kuang Piu
    Chao Kuang Piu was a prominent Hong Kong industrialist and aviation entrepreneur best known for building a major textile empire and helping develop regional air travel in Asia.
  • D. Su Zhu
    Su Zhu is the birth name of Hua Guofeng, the Chinese Communist leader who briefly succeeded Mao Zedong as paramount leader of China in the late 1970s.
  • E. Lao Zai
    Lao Zai is a composer best known for creating the musical score for Zhang Yimou’s 2018 wuxia film "Shadow."
  • 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: Kuo Pao Kun
Triple: [Raffles Institution, hasAlumnus, Kuo Pao Kun]
Generated description
Kuo Pao Kun was a pioneering Singaporean playwright and theatre director widely regarded as a key figure in the development of contemporary theatre in Singapore.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kuo Pao Kun
Target entity description: Kuo Pao Kun was a pioneering Singaporean playwright and theatre director widely regarded as a key figure in the development of contemporary theatre in Singapore.
  • A. Chien-Po
    Chien-Po is a gentle, large, and good-natured warrior from Disney’s Mulan series, known for his calm demeanor and physical strength.
  • B. San Bao
    San Bao is a Chinese composer best known for his film scores and music for director Zhang Yimou’s movies.
  • C. Chao Kuang Piu
    Chao Kuang Piu was a prominent Hong Kong industrialist and aviation entrepreneur best known for building a major textile empire and helping develop regional air travel in Asia.
  • D. Su Zhu
    Su Zhu is the birth name of Hua Guofeng, the Chinese Communist leader who briefly succeeded Mao Zedong as paramount leader of China in the late 1970s.
  • E. Lao Zai
    Lao Zai is a composer best known for creating the musical score for Zhang Yimou’s 2018 wuxia film "Shadow."
  • 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_69d8d38974308190a9174430ef256b73 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e53b032488819098de683bb5c42c4b completed April 19, 2026, 8:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a04f886f2e88190bf01061cb793c0ab completed May 13, 2026, 10:17 p.m.
NEDg Description generation batch_6a04f9511eb08190952be765862cd1ab completed May 13, 2026, 10:21 p.m.
NED2 Entity disambiguation (via description) batch_6a04f9dd338881908b300bab7947f736 completed May 13, 2026, 10:23 p.m.
Created at: April 10, 2026, 11:43 a.m.