Triple

T2732411
Position Surface form Disambiguated ID Type / Status
Subject Elf E60344 entity
Predicate cinematographyBy P1953 FINISHED
Object Greg Gardiner
Greg Gardiner is a film cinematographer best known for his work on the popular Christmas comedy movie "Elf."
E292629 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: Greg Gardiner | Statement: [Elf, cinematographyBy, Greg Gardiner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Greg Gardiner
Context triple: [Elf, cinematographyBy, Greg Gardiner]
  • A. Gerald Hagey
    Gerald Hagey was a Canadian academic and administrator best known as the founding president who led the development of the University of Waterloo into a major institution.
  • B. Tedd Munchak
    Tedd Munchak was an American businessman best known for owning the Carolina Cougars franchise in the former American Basketball Association.
  • C. Ken Anderson
    Ken Anderson was an American animator, art director, and story artist best known for his influential work on numerous classic Walt Disney films.
  • D. Ken Anderson
    Ken Anderson is a former NFL quarterback best known for leading the Cincinnati Bengals in the 1970s and early 1980s, earning an MVP award and a Super Bowl appearance.
  • E. Mike Gartner
    Mike Gartner is a Canadian Hall of Fame right winger renowned as one of the NHL’s most prolific goal scorers, surpassing 700 career goals over a 19-season career.
  • 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: Greg Gardiner
Triple: [Elf, cinematographyBy, Greg Gardiner]
Generated description
Greg Gardiner is a film cinematographer best known for his work on the popular Christmas comedy movie "Elf."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Greg Gardiner
Target entity description: Greg Gardiner is a film cinematographer best known for his work on the popular Christmas comedy movie "Elf."
  • A. Gerald Hagey
    Gerald Hagey was a Canadian academic and administrator best known as the founding president who led the development of the University of Waterloo into a major institution.
  • B. Tedd Munchak
    Tedd Munchak was an American businessman best known for owning the Carolina Cougars franchise in the former American Basketball Association.
  • C. Ken Anderson
    Ken Anderson was an American animator, art director, and story artist best known for his influential work on numerous classic Walt Disney films.
  • D. Ken Anderson
    Ken Anderson is a former NFL quarterback best known for leading the Cincinnati Bengals in the 1970s and early 1980s, earning an MVP award and a Super Bowl appearance.
  • E. Mike Gartner
    Mike Gartner is a Canadian Hall of Fame right winger renowned as one of the NHL’s most prolific goal scorers, surpassing 700 career goals over a 19-season career.
  • 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_69ab4b75cd908190b691ef0d1801acda completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdaf011548190beb9c3feee7b743f completed March 7, 2026, 7:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69afb69eeedc81908ad654de9e1259ea completed March 10, 2026, 6:13 a.m.
NEDg Description generation batch_69afb703a5f8819097b71e19db11feaf completed March 10, 2026, 6:15 a.m.
NED2 Entity disambiguation (via description) batch_69afb7acf3588190813bde4428dfe5f4 completed March 10, 2026, 6:18 a.m.
Created at: March 6, 2026, 9:56 p.m.