Triple

T5107758
Position Surface form Disambiguated ID Type / Status
Subject Amy E115139 entity
Predicate cinematographyBy P1953 FINISHED
Object Adam Goodyer
Adam Goodyer is a cinematographer known for his work on the film "Amy."
 E508204 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: Adam Goodyer | Statement: [Amy, cinematographyBy, Adam Goodyer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Adam Goodyer
Context triple: [Amy, cinematographyBy, Adam Goodyer]
  • A. Alan Wheatley
    Alan Wheatley was a British actor best known for his stage and screen work, including his portrayal of the Sheriff of Nottingham in the 1950s television series "The Adventures of Robin Hood."
  • B. Paul Groves
    Paul Groves is an American operatic tenor acclaimed for his performances in major international opera houses and concert halls.
  • C. Christopher Greenbury
    Christopher Greenbury was a British film editor best known for his Academy Award–winning work on the 1999 drama "American Beauty."
  • D. Martin Boddey
    Martin Boddey was a British character actor known for his frequent supporting roles in mid-20th-century films and television, often portraying authority figures such as policemen and officials.
  • E. David Baulcombe
    David Baulcombe is a British plant scientist renowned for his pioneering work on RNA silencing and gene regulation in plants.
  • 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: Adam Goodyer
Triple: [Amy, cinematographyBy, Adam Goodyer]
Generated description
Adam Goodyer is a cinematographer known for his work on the film "Amy."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Adam Goodyer
Target entity description: Adam Goodyer is a cinematographer known for his work on the film "Amy."
  • A. Alan Wheatley
    Alan Wheatley was a British actor best known for his stage and screen work, including his portrayal of the Sheriff of Nottingham in the 1950s television series "The Adventures of Robin Hood."
  • B. Paul Groves
    Paul Groves is an American operatic tenor acclaimed for his performances in major international opera houses and concert halls.
  • C. Christopher Greenbury
    Christopher Greenbury was a British film editor best known for his Academy Award–winning work on the 1999 drama "American Beauty."
  • D. Martin Boddey
    Martin Boddey was a British character actor known for his frequent supporting roles in mid-20th-century films and television, often portraying authority figures such as policemen and officials.
  • E. David Baulcombe
    David Baulcombe is a British plant scientist renowned for his pioneering work on RNA silencing and gene regulation in plants.
  • 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_69bd4440b3348190be1251fd8b7951f1 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd75a8ee7881908876859402911e5a completed March 20, 2026, 4:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf06a25110819080a4cbd13555e652 completed March 21, 2026, 8:59 p.m.
NEDg Description generation batch_69bf078fc07c819080191ec98bca4c71 completed March 21, 2026, 9:03 p.m.
NED2 Entity disambiguation (via description) batch_69bf07e20ad48190ba25294e1971e768 completed March 21, 2026, 9:04 p.m.
Created at: March 20, 2026, 1:41 p.m.