Triple

T14847406
Position Surface form Disambiguated ID Type / Status
Subject Clive Swift E349133 entity
Predicate notableRole P22 FINISHED
Object Richard Bucket
Richard Bucket is the long-suffering, socially anxious husband of Hyacinth in the British sitcom "Keeping Up Appearances."
E1124509 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: Richard Bucket | Statement: [Clive Swift, notableRole, Richard Bucket]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Richard Bucket
Context triple: [Clive Swift, notableRole, Richard Bucket]
  • A. Jonathan Oldbuck
    Jonathan Oldbuck is a fictional, eccentric antiquary and amateur historian who serves as the central figure in Sir Walter Scott’s novel "The Antiquary."
  • B. Albert Narracott
    Albert Narracott is the young English farm boy whose deep bond with his horse Joey drives the emotional core of Michael Morpurgo’s World War I novel "War Horse."
  • C. Henry Biggs
    Henry Biggs is a central character in the film "The Preacher's Wife," portrayed as a devoted pastor whose strained marriage and crisis of faith draw the attention of a visiting angel.
  • D. Philip Voyzey
    Philip Voyzey was an actor who appeared in the classic 1950 film "All About Eve."
  • E. Ted Buckland
    Ted Buckland is a neurotic, often bumbling hospital lawyer from the TV series "Scrubs," known for his awkward behavior and unrequited crushes.
  • 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: Richard Bucket
Triple: [Clive Swift, notableRole, Richard Bucket]
Generated description
Richard Bucket is the long-suffering, socially anxious husband of Hyacinth in the British sitcom "Keeping Up Appearances."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Richard Bucket
Target entity description: Richard Bucket is the long-suffering, socially anxious husband of Hyacinth in the British sitcom "Keeping Up Appearances."
  • A. Jonathan Oldbuck
    Jonathan Oldbuck is a fictional, eccentric antiquary and amateur historian who serves as the central figure in Sir Walter Scott’s novel "The Antiquary."
  • B. Albert Narracott
    Albert Narracott is the young English farm boy whose deep bond with his horse Joey drives the emotional core of Michael Morpurgo’s World War I novel "War Horse."
  • C. Henry Biggs
    Henry Biggs is a central character in the film "The Preacher's Wife," portrayed as a devoted pastor whose strained marriage and crisis of faith draw the attention of a visiting angel.
  • D. Philip Voyzey
    Philip Voyzey was an actor who appeared in the classic 1950 film "All About Eve."
  • E. Ted Buckland
    Ted Buckland is a neurotic, often bumbling hospital lawyer from the TV series "Scrubs," known for his awkward behavior and unrequited crushes.
  • 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_69d822ec69008190a9232caa68836872 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded29236dc8190b7d3a37d09f9fb21 completed April 14, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe6502d3f081909ff6fa8722769e2e completed May 8, 2026, 10:34 p.m.
NEDg Description generation batch_69fe662fa374819083367ba7f9da2272 completed May 8, 2026, 10:39 p.m.
NED2 Entity disambiguation (via description) batch_69fe67664044819084196e3e6e365415 completed May 8, 2026, 10:44 p.m.
Created at: April 10, 2026, 1:53 a.m.