Triple

T387352
Position Surface form Disambiguated ID Type / Status
Subject Emanuel School E8806 entity
Predicate hasNotableAlumnus P51 FINISHED
Object Lennox Cato
Lennox Cato is a British antiques dealer and television expert best known for his appearances on the BBC’s "Antiques Roadshow."
E53459 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: Lennox Cato | Statement: [Emanuel School, hasNotableAlumnus, Lennox Cato]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lennox Cato
Context triple: [Emanuel School, hasNotableAlumnus, Lennox Cato]
  • A. Roland Caulder
    Roland Caulder is an actor known for his role in the film "The Iron Mask."
  • B. Roderick
    Roderick is the full given name of Rod Langway, a Hall of Fame former professional ice hockey defenseman best known for his time with the Washington Capitals.
  • C. Julian Burnside
    Julian Burnside is an Australian barrister and human rights advocate renowned for his work defending refugees and speaking out on civil liberties and social justice.
  • D. Cecil
    Cecil is a masculine given name most famously associated with pioneering American film director and producer Cecil B. DeMille.
  • E. Clive
    Clive is a surname most famously associated with Robert Clive, the 18th-century British officer who played a key role in establishing British rule in India.
  • 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: Lennox Cato
Triple: [Emanuel School, hasNotableAlumnus, Lennox Cato]
Generated description
Lennox Cato is a British antiques dealer and television expert best known for his appearances on the BBC’s "Antiques Roadshow."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lennox Cato
Target entity description: Lennox Cato is a British antiques dealer and television expert best known for his appearances on the BBC’s "Antiques Roadshow."
  • A. Roland Caulder
    Roland Caulder is an actor known for his role in the film "The Iron Mask."
  • B. Roderick
    Roderick is the full given name of Rod Langway, a Hall of Fame former professional ice hockey defenseman best known for his time with the Washington Capitals.
  • C. Julian Burnside
    Julian Burnside is an Australian barrister and human rights advocate renowned for his work defending refugees and speaking out on civil liberties and social justice.
  • D. Cecil
    Cecil is a masculine given name most famously associated with pioneering American film director and producer Cecil B. DeMille.
  • E. Clive
    Clive is a surname most famously associated with Robert Clive, the 18th-century British officer who played a key role in establishing British rule in India.
  • 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_69a2e7f55c60819097aff65ea2ca2832 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ec5828d881909e8810061c02480c completed Feb. 28, 2026, 1:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4253ec4d48190bdaaf385c9a8e4a9 completed March 1, 2026, 11:38 a.m.
NEDg Description generation batch_69a42919a09c819094b41c333bb1aa2e completed March 1, 2026, 11:55 a.m.
NED2 Entity disambiguation (via description) batch_69a4296cb3f48190b56227620ce5ce59 completed March 1, 2026, 11:56 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.