Triple

T14593283
Position Surface form Disambiguated ID Type / Status
Subject Gogglebox E342498 entity
Predicate creator P184 FINISHED
Object Stephen Lambert
Stephen Lambert is a British television producer and executive known for creating popular reality and factual entertainment formats such as "Gogglebox."
E1109433 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: Stephen Lambert | Statement: [Gogglebox, creator, Stephen Lambert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stephen Lambert
Context triple: [Gogglebox, creator, Stephen Lambert]
  • A. Scott Lambert
    Scott Lambert is a film producer known for his work on the drama film "North Country."
  • B. Scott Lambert
    Scott Lambert is a film and television producer known for his work on projects such as the movie "The Silence."
  • C. Scott Lambert
    Scott Lambert is a film producer known for his work on acclaimed projects including the psychological drama "Tár."
  • D. Gary Lambert
    Gary Lambert is a central figure in Jonathan Franzen's novel "The Corrections," portrayed as an anxious, financially driven Midwestern son struggling with family expectations and personal dissatisfaction.
  • E. Michael Harnett
    Michael Harnett is the birth name of Michael Hartnett, a prominent Irish poet known for his lyrical work in both English and Irish.
  • 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: Stephen Lambert
Triple: [Gogglebox, creator, Stephen Lambert]
Generated description
Stephen Lambert is a British television producer and executive known for creating popular reality and factual entertainment formats such as "Gogglebox."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Stephen Lambert
Target entity description: Stephen Lambert is a British television producer and executive known for creating popular reality and factual entertainment formats such as "Gogglebox."
  • A. Scott Lambert
    Scott Lambert is a film producer known for his work on the drama film "North Country."
  • B. Scott Lambert
    Scott Lambert is a film and television producer known for his work on projects such as the movie "The Silence."
  • C. Scott Lambert
    Scott Lambert is a film producer known for his work on acclaimed projects including the psychological drama "Tár."
  • D. Gary Lambert
    Gary Lambert is a central figure in Jonathan Franzen's novel "The Corrections," portrayed as an anxious, financially driven Midwestern son struggling with family expectations and personal dissatisfaction.
  • E. Michael Harnett
    Michael Harnett is the birth name of Michael Hartnett, a prominent Irish poet known for his lyrical work in both English and Irish.
  • 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_69d822ddc0f081909cd8163c7de298cd completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb43480d8819084a707e56da2c237 completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fda918542c819099646943be59dd04 completed May 8, 2026, 9:12 a.m.
NEDg Description generation batch_69fdaed912d4819088c4b96c56187044 completed May 8, 2026, 9:37 a.m.
NED2 Entity disambiguation (via description) batch_69fdaf8104588190b76ff363367b8f78 completed May 8, 2026, 9:40 a.m.
Created at: April 10, 2026, 1:24 a.m.