Triple

T20416798
Position Surface form Disambiguated ID Type / Status
Subject Detection Club E500732 entity
Predicate hasMember P10 FINISHED
Object Nicola Upson
Nicola Upson is a British crime novelist best known for her historical mystery series featuring real-life author Josephine Tey as a detective.
E1428912 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: Nicola Upson | Statement: [Detection Club, hasMember, Nicola Upson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nicola Upson
Context triple: [Detection Club, hasMember, Nicola Upson]
  • A. Nicola Harrison
    Nicola Harrison is an actress known for her role in the 2017 gothic horror film "Marrowbone."
  • B. Nicola Reynolds
    Nicola Reynolds is a Welsh actress best known for her role in the cult British film "Human Traffic" and for her work in UK television and theatre.
  • C. Nicola Beauman
    Nicola Beauman is a British biographer, literary historian, and founder of the feminist publishing house Persephone Books, known for reviving neglected works by 20th-century women writers.
  • D. Nicola Duffett
    Nicola Duffett is a British actress known for her work in television, film, and theatre, including roles in popular UK dramas and soap operas.
  • E. Nicola Scott
    Nicola Scott is the daughter of English novelist Elizabeth Jane Howard.
  • 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: Nicola Upson
Triple: [Detection Club, hasMember, Nicola Upson]
Generated description
Nicola Upson is a British crime novelist best known for her historical mystery series featuring real-life author Josephine Tey as a detective.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nicola Upson
Target entity description: Nicola Upson is a British crime novelist best known for her historical mystery series featuring real-life author Josephine Tey as a detective.
  • A. Nicola Harrison
    Nicola Harrison is an actress known for her role in the 2017 gothic horror film "Marrowbone."
  • B. Nicola Reynolds
    Nicola Reynolds is a Welsh actress best known for her role in the cult British film "Human Traffic" and for her work in UK television and theatre.
  • C. Nicola Beauman
    Nicola Beauman is a British biographer, literary historian, and founder of the feminist publishing house Persephone Books, known for reviving neglected works by 20th-century women writers.
  • D. Nicola Duffett
    Nicola Duffett is a British actress known for her work in television, film, and theatre, including roles in popular UK dramas and soap operas.
  • E. Nicola Scott
    Nicola Scott is the daughter of English novelist Elizabeth Jane Howard.
  • 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.