Triple

T1801105
Position Surface form Disambiguated ID Type / Status
Subject Trouble in Store E39719 entity
Predicate cinematography P1953 FINISHED
Object Gordon Dines
Gordon Dines was a British cinematographer known for his work on mid-20th-century films, particularly comedies and dramas.
E272578 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: Gordon Dines | Statement: [Trouble in Store, cinematography, Gordon Dines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gordon Dines
Context triple: [Trouble in Store, cinematography, Gordon Dines]
  • A. Gordon Davis
    Gordon Davis is a pseudonym used by E. Howard Hunt, the American intelligence officer and author involved in the Watergate scandal.
  • B. Gordon Bowker
    Gordon Bowker is an American writer and entrepreneur best known as one of the co-founders of the global coffee company Starbucks.
  • C. Denis Barnett
    Denis Barnett was a senior Royal Air Force officer who rose to high command during and after the Second World War.
  • D. Gordon Mitchell
    Gordon Mitchell is the son of renowned British aeronautical engineer R. J. Mitchell, designer of the Supermarine Spitfire.
  • E. Gordon Coates
    Gordon Coates was a New Zealand politician who served as Prime Minister in the 1920s and played a key role in shaping the country's policies within the British Empire and later the Commonwealth.
  • 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: Gordon Dines
Triple: [Trouble in Store, cinematography, Gordon Dines]
Generated description
Gordon Dines was a British cinematographer known for his work on mid-20th-century films, particularly comedies and dramas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Gordon Dines
Target entity description: Gordon Dines was a British cinematographer known for his work on mid-20th-century films, particularly comedies and dramas.
  • A. Gordon Davis
    Gordon Davis is a pseudonym used by E. Howard Hunt, the American intelligence officer and author involved in the Watergate scandal.
  • B. Gordon Bowker
    Gordon Bowker is an American writer and entrepreneur best known as one of the co-founders of the global coffee company Starbucks.
  • C. Denis Barnett
    Denis Barnett was a senior Royal Air Force officer who rose to high command during and after the Second World War.
  • D. Gordon Mitchell
    Gordon Mitchell is the son of renowned British aeronautical engineer R. J. Mitchell, designer of the Supermarine Spitfire.
  • E. Gordon Coates
    Gordon Coates was a New Zealand politician who served as Prime Minister in the 1920s and played a key role in shaping the country's policies within the British Empire and later the Commonwealth.
  • 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_69a88632aa588190ba3978fde0db5bbd completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa656ad5d4819090e677ad137b0cd1 completed March 6, 2026, 5:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69af1f6cb97c8190bf6e8dbdcae3aabd completed March 9, 2026, 7:28 p.m.
NEDg Description generation batch_69af201e1a748190905bb221fc5dd01e completed March 9, 2026, 7:31 p.m.
NED2 Entity disambiguation (via description) batch_69af20ad25588190b8e26e82baba731d completed March 9, 2026, 7:34 p.m.
Created at: March 4, 2026, 7:32 p.m.