Triple

T11171511
Position Surface form Disambiguated ID Type / Status
Subject Judge Turpin E264283 entity
Predicate enemyOf P437 FINISHED
Object Benjamin Barker
Benjamin Barker is the wrongfully imprisoned barber who returns to London under the alias Sweeney Todd to seek revenge in Stephen Sondheim’s musical and its adaptations.
E908922 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: Benjamin Barker | Statement: [Judge Turpin, enemyOf, Benjamin Barker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Benjamin Barker
Context triple: [Judge Turpin, enemyOf, Benjamin Barker]
  • A. Will Turpin
    Will Turpin is an American musician best known as the longtime bassist for the rock band Collective Soul.
  • B. Roger the Dodger
    Roger the Dodger is the famed Hall of Fame NFL quarterback Roger Staubach, celebrated for his elusive scrambling ability and clutch performances with the Dallas Cowboys.
  • C. Marty Fogg
    Marty Fogg is a musician and composer known for creating the music for the song "I'm Still Here."
  • D. Simon Farnaby
    Simon Farnaby is a British actor, comedian, and screenwriter known for his work on projects like Paddington 2, Ghosts, and Horrible Histories.
  • E. Oliver Braddick
    Oliver Braddick is a British experimental psychologist and neuroscientist known for his influential work on visual perception and development.
  • 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: Benjamin Barker
Triple: [Judge Turpin, enemyOf, Benjamin Barker]
Generated description
Benjamin Barker is the wrongfully imprisoned barber who returns to London under the alias Sweeney Todd to seek revenge in Stephen Sondheim’s musical and its adaptations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Benjamin Barker
Target entity description: Benjamin Barker is the wrongfully imprisoned barber who returns to London under the alias Sweeney Todd to seek revenge in Stephen Sondheim’s musical and its adaptations.
  • A. Will Turpin
    Will Turpin is an American musician best known as the longtime bassist for the rock band Collective Soul.
  • B. Roger the Dodger
    Roger the Dodger is the famed Hall of Fame NFL quarterback Roger Staubach, celebrated for his elusive scrambling ability and clutch performances with the Dallas Cowboys.
  • C. Marty Fogg
    Marty Fogg is a musician and composer known for creating the music for the song "I'm Still Here."
  • D. Simon Farnaby
    Simon Farnaby is a British actor, comedian, and screenwriter known for his work on projects like Paddington 2, Ghosts, and Horrible Histories.
  • E. Oliver Braddick
    Oliver Braddick is a British experimental psychologist and neuroscientist known for his influential work on visual perception and development.
  • 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_69d6aa9dafac8190bd90d2c74f661aa7 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e89660208190b1d9e91529f5d246 completed April 9, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69e463b155a08190b361b38a39d25b1f completed April 19, 2026, 5:10 a.m.
NEDg Description generation batch_69e46c37efec81908aa709587c37569d completed April 19, 2026, 5:46 a.m.
NED2 Entity disambiguation (via description) batch_69e47292cdd08190b05c4c8b09f4f918 completed April 19, 2026, 6:13 a.m.
Created at: April 8, 2026, 9:29 p.m.