Triple

T577986
Position Surface form Disambiguated ID Type / Status
Subject Frost/Nixon E13797 entity
Predicate editor P1954 FINISHED
Object Dan Hanley
Dan Hanley is an American film editor best known for his long-time collaboration with director Ron Howard on numerous major Hollywood films.
 E202037 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: Dan Hanley | Statement: [Frost/Nixon, editor, Dan Hanley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dan Hanley
Context triple: [Frost/Nixon, editor, Dan Hanley]
  • A. Jeff Henley
    Jeff Henley is an American business executive best known for his long tenure as Oracle Corporation’s chief financial officer and later chairman of the board.
  • B. Mark Herron
    Mark Herron was an American actor best known for being the fourth husband of legendary entertainer Judy Garland.
  • C. Graeme Revell
    Graeme Revell is a New Zealand-born composer best known for his atmospheric film scores across genres including horror, action, and science fiction.
  • D. Derek Dowding
    Derek Dowding was a Royal Air Force officer and the son of Air Chief Marshal Hugh Dowding, noted for his own distinguished service in military aviation.
  • E. Andrew Humphrey
    Andrew Humphrey was a senior Royal Air Force officer who rose to become Chief of the Air Staff and later Chief of the Defence Staff in the United Kingdom.
  • 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: Dan Hanley
Triple: [Frost/Nixon, editor, Dan Hanley]
Generated description
Dan Hanley is an American film editor best known for his long-time collaboration with director Ron Howard on numerous major Hollywood films.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dan Hanley
Target entity description: Dan Hanley is an American film editor best known for his long-time collaboration with director Ron Howard on numerous major Hollywood films.
  • A. Jeff Henley
    Jeff Henley is an American business executive best known for his long tenure as Oracle Corporation’s chief financial officer and later chairman of the board.
  • B. Mark Herron
    Mark Herron was an American actor best known for being the fourth husband of legendary entertainer Judy Garland.
  • C. Graeme Revell
    Graeme Revell is a New Zealand-born composer best known for his atmospheric film scores across genres including horror, action, and science fiction.
  • D. Derek Dowding
    Derek Dowding was a Royal Air Force officer and the son of Air Chief Marshal Hugh Dowding, noted for his own distinguished service in military aviation.
  • E. Andrew Humphrey
    Andrew Humphrey was a senior Royal Air Force officer who rose to become Chief of the Air Staff and later Chief of the Defence Staff in the United Kingdom.
  • 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_69a4933fa4d88190a7949cc83c08c5c1 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49b69fed88190b5558d4ebd5047a1 completed March 1, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69adb5a101108190897a066413a3b6a1 completed March 8, 2026, 5:45 p.m.
NEDg Description generation batch_69adb8b2b01c8190997179cdfd55da13 completed March 8, 2026, 5:58 p.m.
NED2 Entity disambiguation (via description) batch_69adb94aaf348190a28ca8e9d9cacf41 completed March 8, 2026, 6 p.m.
Created at: March 1, 2026, 7:33 p.m.