Triple

T14238565
Position Surface form Disambiguated ID Type / Status
Subject Sergeant Benton E352949 entity
Predicate portrayedBy P1507 FINISHED
Object John Levene
John Levene is a British actor best known for playing UNIT soldier Sergeant Benton in the classic science fiction television series Doctor Who.
E1139656 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: John Levene | Statement: [Sergeant Benton, portrayedBy, John Levene]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Levene
Context triple: [Sergeant Benton, portrayedBy, John Levene]
  • A. Philip Levene
    Philip Levene was a British television and film writer best known for his work on the 1960s spy series "The Avengers."
  • B. Sam Levene
    Sam Levene was a prominent American stage and film actor best known for his comic and character roles in mid-20th-century Broadway productions and Hollywood movies.
  • C. Sam Levine
    Sam Levine is an American animation director and storyboard artist known for co-directing the superhero comedy film "DC League of Super-Pets."
  • D. Gene Levitt
    Gene Levitt was an American television writer and producer best known for creating the popular 1970s–80s anthology series "Fantasy Island."
  • E. Leo Salkin
    Leo Salkin was an American animator, writer, and storyboard artist known for his work on mid-20th-century animated films and shorts.
  • 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: John Levene
Triple: [Sergeant Benton, portrayedBy, John Levene]
Generated description
John Levene is a British actor best known for playing UNIT soldier Sergeant Benton in the classic science fiction television series Doctor Who.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John Levene
Target entity description: John Levene is a British actor best known for playing UNIT soldier Sergeant Benton in the classic science fiction television series Doctor Who.
  • A. Philip Levene
    Philip Levene was a British television and film writer best known for his work on the 1960s spy series "The Avengers."
  • B. Sam Levene
    Sam Levene was a prominent American stage and film actor best known for his comic and character roles in mid-20th-century Broadway productions and Hollywood movies.
  • C. Sam Levine
    Sam Levine is an American animation director and storyboard artist known for co-directing the superhero comedy film "DC League of Super-Pets."
  • D. Gene Levitt
    Gene Levitt was an American television writer and producer best known for creating the popular 1970s–80s anthology series "Fantasy Island."
  • E. Leo Salkin
    Leo Salkin was an American animator, writer, and storyboard artist known for his work on mid-20th-century animated films and shorts.
  • 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_69d8278adc7c8190a9218d69bce3c4e6 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de62432fb48190b153805b85c4f2d2 completed April 14, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69febfcd67f081909f97bcf38d814a13 completed May 9, 2026, 5:02 a.m.
NEDg Description generation batch_69fec04c1f1c8190bbd2ada725505ca6 completed May 9, 2026, 5:04 a.m.
NED2 Entity disambiguation (via description) batch_69fec0da6e54819090f25bd0eee128d6 completed May 9, 2026, 5:06 a.m.
Created at: April 10, 2026, 1:08 a.m.