Triple

T20416795
Position Surface form Disambiguated ID Type / Status
Subject Detection Club E500732 entity
Predicate hasMember P10 FINISHED
Object Vaseem Khan
Vaseem Khan is a British crime fiction author best known for his Baby Ganesh Agency series set in India and his Malabar House historical crime novels.
E1428910 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: Vaseem Khan | Statement: [Detection Club, hasMember, Vaseem Khan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vaseem Khan
Context triple: [Detection Club, hasMember, Vaseem Khan]
  • A. Arif Masood
    Arif Masood is a Pakistani architect best known for designing the iconic Pakistan Monument in Islamabad.
  • B. Shehzad Khan
    Shehzad Khan is an Indian film and television actor best known for his supporting and comic roles in Hindi cinema, including the classic romance "Qayamat Se Qayamat Tak."
  • C. Azim Surani
    Azim Surani is a British developmental biologist renowned for his pioneering work on mammalian germ cell development and genomic imprinting.
  • D. Arshad Khan
    Arshad Khan was a victim killed during the 2011 U.S. special forces raid in Abbottabad, Pakistan, that targeted Osama bin Laden.
  • E. Sunny Khan
    Sunny Khan is a central detective character in the British crime drama series "Unforgotten," known for his methodical investigative style and partnership with lead detective Cassie Stuart.
  • 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: Vaseem Khan
Triple: [Detection Club, hasMember, Vaseem Khan]
Generated description
Vaseem Khan is a British crime fiction author best known for his Baby Ganesh Agency series set in India and his Malabar House historical crime novels.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Vaseem Khan
Target entity description: Vaseem Khan is a British crime fiction author best known for his Baby Ganesh Agency series set in India and his Malabar House historical crime novels.
  • A. Arif Masood
    Arif Masood is a Pakistani architect best known for designing the iconic Pakistan Monument in Islamabad.
  • B. Shehzad Khan
    Shehzad Khan is an Indian film and television actor best known for his supporting and comic roles in Hindi cinema, including the classic romance "Qayamat Se Qayamat Tak."
  • C. Azim Surani
    Azim Surani is a British developmental biologist renowned for his pioneering work on mammalian germ cell development and genomic imprinting.
  • D. Arshad Khan
    Arshad Khan was a victim killed during the 2011 U.S. special forces raid in Abbottabad, Pakistan, that targeted Osama bin Laden.
  • E. Sunny Khan
    Sunny Khan is a central detective character in the British crime drama series "Unforgotten," known for his methodical investigative style and partnership with lead detective Cassie Stuart.
  • 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_69e0b4a935588190b9446a99b37ced44 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e67a4437448190b07b6e6e3de5830f completed April 20, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a087b284bb8819090f76ec27116c619 completed May 16, 2026, 2:11 p.m.
NEDg Description generation batch_6a088017be588190ab94b8180e44ebf4 completed May 16, 2026, 2:32 p.m.
NED2 Entity disambiguation (via description) batch_6a0880c45e1081908f439ade0c31a47e completed May 16, 2026, 2:35 p.m.
Created at: April 16, 2026, 11:30 a.m.