Triple

T17075090
Position Surface form Disambiguated ID Type / Status
Subject Diocesan Boys’ School E414326 entity
Predicate hasAlumnus P51 FINISHED
Object Alan Leong
Alan Leong is a Hong Kong barrister and pro-democracy politician known for his leadership in the Civic Party and his candidacy in the 2007 Chief Executive election.
 E1304629 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: Alan Leong | Statement: [Diocesan Boys’ School, hasAlumnus, Alan Leong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Alan Leong
Context triple: [Diocesan Boys’ School, hasAlumnus, Alan Leong]
  • A. Alvin Leong
    Alvin Leong is a music producer known for his work on the song "Shall We Talk."
  • B. Victor Wong
    Victor Wong was an American character actor known for his distinctive presence in films such as "The Last Emperor," "Big Trouble in Little China," and "Tremors."
  • C. Arthur Wong
    Arthur Wong is a renowned Hong Kong cinematographer known for his work on numerous action and martial arts films.
  • D. Stephen Wong
    Stephen Wong is a technology entrepreneur best known as a founder of the software company Embarcadero Technologies.
  • E. Jim Cheung
    Jim Cheung is a British comic book artist best known for his detailed, dynamic work on major Marvel titles such as Young Avengers and various large-scale crossover events.
  • 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: Alan Leong
Triple: [Diocesan Boys’ School, hasAlumnus, Alan Leong]
Generated description
Alan Leong is a Hong Kong barrister and pro-democracy politician known for his leadership in the Civic Party and his candidacy in the 2007 Chief Executive election.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Alan Leong
Target entity description: Alan Leong is a Hong Kong barrister and pro-democracy politician known for his leadership in the Civic Party and his candidacy in the 2007 Chief Executive election.
  • A. Alvin Leong
    Alvin Leong is a music producer known for his work on the song "Shall We Talk."
  • B. Victor Wong
    Victor Wong was an American character actor known for his distinctive presence in films such as "The Last Emperor," "Big Trouble in Little China," and "Tremors."
  • C. Arthur Wong
    Arthur Wong is a renowned Hong Kong cinematographer known for his work on numerous action and martial arts films.
  • D. Stephen Wong
    Stephen Wong is a technology entrepreneur best known as a founder of the software company Embarcadero Technologies.
  • E. Jim Cheung
    Jim Cheung is a British comic book artist best known for his detailed, dynamic work on major Marvel titles such as Young Avengers and various large-scale crossover events.
  • 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_69d886cef44c8190ba56c44b4e863e64 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3dbc47808819088a4ca039689b213 completed April 18, 2026, 7:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a035d74c65c8190ac966c1fb96b0ce1 completed May 12, 2026, 5:03 p.m.
NEDg Description generation batch_6a035e8347608190a224143b51cfb68a completed May 12, 2026, 5:08 p.m.
NED2 Entity disambiguation (via description) batch_6a035f05ed748190adecfab4c60397e4 completed May 12, 2026, 5:10 p.m.
Created at: April 10, 2026, 5:34 a.m.