Triple

T9237917
Position Surface form Disambiguated ID Type / Status
Subject Hamburger Hill E221982 entity
Predicate editedBy P1954 FINISHED
Object Peter Tanner
Peter Tanner was a British film editor known for his work on numerous feature films, including the Vietnam War drama "Hamburger Hill."
 E787144 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: Peter Tanner | Statement: [Hamburger Hill, editedBy, Peter Tanner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Peter Tanner
Context triple: [Hamburger Hill, editedBy, Peter Tanner]
  • A. John Todd
    John Todd was a British mathematician known for his work in numerical analysis and for helping to establish the field of computational mathematics.
  • B. John Todd
    John Todd is a prominent member of the Todd family, recognized for his significant role and influence within this historically notable lineage.
  • C. Peter Howard
    Peter Howard was a prominent American musical theatre orchestrator and dance music arranger known for his work on numerous Broadway productions.
  • D. Mike Talman
    Mike Talman is a con man who becomes entangled in a tense scheme involving a blind woman and hidden heroin in the thriller "Wait Until Dark."
  • E. Peter Garnsey
    Peter Garnsey is a prominent historian of the ancient world, particularly known for his influential scholarship on the social, economic, and legal history of the Roman Empire.
  • 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: Peter Tanner
Triple: [Hamburger Hill, editedBy, Peter Tanner]
Generated description
Peter Tanner was a British film editor known for his work on numerous feature films, including the Vietnam War drama "Hamburger Hill."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Peter Tanner
Target entity description: Peter Tanner was a British film editor known for his work on numerous feature films, including the Vietnam War drama "Hamburger Hill."
  • A. John Todd
    John Todd was a British mathematician known for his work in numerical analysis and for helping to establish the field of computational mathematics.
  • B. John Todd
    John Todd is a prominent member of the Todd family, recognized for his significant role and influence within this historically notable lineage.
  • C. Peter Howard
    Peter Howard was a prominent American musical theatre orchestrator and dance music arranger known for his work on numerous Broadway productions.
  • D. Mike Talman
    Mike Talman is a con man who becomes entangled in a tense scheme involving a blind woman and hidden heroin in the thriller "Wait Until Dark."
  • E. Peter Garnsey
    Peter Garnsey is a prominent historian of the ancient world, particularly known for his influential scholarship on the social, economic, and legal history of the Roman Empire.
  • 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_69ca83ee26cc81909ac624e190597d6d completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccf09f9e908190801fe114c5e63984 completed April 1, 2026, 10:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69d077d4c4a881909c80176ddf5101a4 completed April 4, 2026, 2:30 a.m.
NEDg Description generation batch_69d07da85c748190ab7096ce3d3d2319 completed April 4, 2026, 2:55 a.m.
NED2 Entity disambiguation (via description) batch_69d07e52c0788190a5009a7fe649a6c7 completed April 4, 2026, 2:58 a.m.
Created at: March 30, 2026, 7:30 p.m.