Triple

T18572343
Position Surface form Disambiguated ID Type / Status
Subject Raffles Institution E453901 entity
Predicate hasAlumnus P51 FINISHED
Object Mark Lee
Mark Lee is a Singaporean comedian, actor, and television host known for his work in local films and variety shows.
 E1333539 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: Mark Lee | Statement: [Raffles Institution, hasAlumnus, Mark Lee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mark Lee
Context triple: [Raffles Institution, hasAlumnus, Mark Lee]
  • A. Mark Lee
    Mark Lee is an Australian actor best known for his leading role in the acclaimed World War I film "Gallipoli."
  • B. Mark Lee
    Mark Lee is a prominent contemporary architect known for his minimalist, context-sensitive designs and leadership of the Los Angeles–based firm Johnston Marklee.
  • C. Marc Lee
    Marc Lee is a U.S. Navy SEAL and close comrade of Chris Kyle who is depicted as a key supporting character in the film "American Sniper."
  • D. Jack Lee
    Jack Lee was a British film director best known for his work on mid-20th-century dramas and war films.
  • E. Jay Lee
    Jay Lee is an actor best known for his role in the television miniseries adaptation of John Green's novel "Looking for Alaska."
  • 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: Mark Lee
Triple: [Raffles Institution, hasAlumnus, Mark Lee]
Generated description
Mark Lee is a Singaporean comedian, actor, and television host known for his work in local films and variety shows.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mark Lee
Target entity description: Mark Lee is a Singaporean comedian, actor, and television host known for his work in local films and variety shows.
  • A. Mark Lee
    Mark Lee is an Australian actor best known for his leading role in the acclaimed World War I film "Gallipoli."
  • B. Mark Lee
    Mark Lee is a prominent contemporary architect known for his minimalist, context-sensitive designs and leadership of the Los Angeles–based firm Johnston Marklee.
  • C. Marc Lee
    Marc Lee is a U.S. Navy SEAL and close comrade of Chris Kyle who is depicted as a key supporting character in the film "American Sniper."
  • D. Jack Lee
    Jack Lee was a British film director best known for his work on mid-20th-century dramas and war films.
  • E. Jay Lee
    Jay Lee is an actor best known for his role in the television miniseries adaptation of John Green's novel "Looking for Alaska."
  • 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_6a0503761830819088f36a34e377ff49 completed May 13, 2026, 11:04 p.m.
NEDg Description generation batch_6a050537da5481908da9209410986124 completed May 13, 2026, 11:11 p.m.
NED2 Entity disambiguation (via description) batch_6a0505e91794819086506a77ef287645 completed May 13, 2026, 11:14 p.m.
Created at: April 10, 2026, 11:43 a.m.