Triple

T17857782
Position Surface form Disambiguated ID Type / Status
Subject Arthur Margetson E445983 entity
Predicate notableWork P4 FINISHED
Object The House of Traps
The House of Traps is a British mystery film in which Arthur Margetson played a prominent role.
 E1292801 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: The House of Traps | Statement: [Arthur Margetson, notableWork, The House of Traps]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: The House of Traps
Context triple: [Arthur Margetson, notableWork, The House of Traps]
  • A. The Gentle Trap
    The Gentle Trap is a 1960 British crime drama film best known for featuring actress Patricia Dainton in a leading role.
  • B. The Steel Trap
    The Steel Trap is a 1952 American crime thriller film starring Joseph Cotten as a bank employee who devises a plan to steal money and flee the country.
  • C. The Trap
    "The Trap" is a horror novel by Tabitha King that delves into psychological terror and the darker sides of human relationships in a small-town setting.
  • D. The Trap
    The Trap is a 1966 British adventure drama film set in the Canadian wilderness, starring Rita Tushingham and Oliver Reed.
  • E. The Demon Trap
    The Demon Trap is a science fiction short story by Peter F. Hamilton set in his Commonwealth universe and collected in the anthology Manhattan in Reverse.
  • 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: The House of Traps
Triple: [Arthur Margetson, notableWork, The House of Traps]
Generated description
The House of Traps is a British mystery film in which Arthur Margetson played a prominent role.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: The House of Traps
Target entity description: The House of Traps is a British mystery film in which Arthur Margetson played a prominent role.
  • A. The Gentle Trap
    The Gentle Trap is a 1960 British crime drama film best known for featuring actress Patricia Dainton in a leading role.
  • B. The Steel Trap
    The Steel Trap is a 1952 American crime thriller film starring Joseph Cotten as a bank employee who devises a plan to steal money and flee the country.
  • C. The Trap
    "The Trap" is a horror novel by Tabitha King that delves into psychological terror and the darker sides of human relationships in a small-town setting.
  • D. The Trap
    The Trap is a 1966 British adventure drama film set in the Canadian wilderness, starring Rita Tushingham and Oliver Reed.
  • E. The Demon Trap
    The Demon Trap is a science fiction short story by Peter F. Hamilton set in his Commonwealth universe and collected in the anthology Manhattan in Reverse.
  • 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_69d8b9f26f18819089c9e43250bee6ae completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4978d05708190838386d37eb157bc completed April 19, 2026, 8:51 a.m.
NED1 Entity disambiguation (via context triple) batch_6a030c640bb881909fea3f07e5a30f7a completed May 12, 2026, 11:17 a.m.
NEDg Description generation batch_6a03102824a081909f7e6253f067f9ec completed May 12, 2026, 11:34 a.m.
NED2 Entity disambiguation (via description) batch_6a0310bc396881908988dd6e776ecc23 completed May 12, 2026, 11:36 a.m.
Created at: April 10, 2026, 10:17 a.m.