Triple

T10793939
Position Surface form Disambiguated ID Type / Status
Subject Jeff Cronenweth E254654 entity
Predicate familyName P18 FINISHED
Object Cronenweth
Cronenweth is a surname most notably associated with a family of acclaimed American cinematographers, including Jeff Cronenweth and his father Jordan Cronenweth.
 E885462 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: Cronenweth | Statement: [Jeff Cronenweth, familyName, Cronenweth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Cronenweth
Context triple: [Jeff Cronenweth, familyName, Cronenweth]
  • A. Corrsin
    Corrsin is a surname most notably associated with Stanley Corrsin, an influential American fluid dynamicist known for his work on turbulence.
  • B. Calbraith
    Calbraith is the middle name of U.S. naval officer Matthew Calbraith Perry, known for opening Japan to Western trade in the mid-19th century.
  • C. Essenrode
    Essenrode is a small village in Lower Saxony, Germany, historically associated with the noble von Hardenberg family.
  • D. Gwathmey
    Gwathmey is the surname of Charles Gwathmey, a prominent American architect known for his influential modernist designs.
  • E. Yarrowitch
    Yarrowitch is a small rural locality in New South Wales, Australia, known for its agricultural landscape and proximity to national parks and natural attractions.
  • 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: Cronenweth
Triple: [Jeff Cronenweth, familyName, Cronenweth]
Generated description
Cronenweth is a surname most notably associated with a family of acclaimed American cinematographers, including Jeff Cronenweth and his father Jordan Cronenweth.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Cronenweth
Target entity description: Cronenweth is a surname most notably associated with a family of acclaimed American cinematographers, including Jeff Cronenweth and his father Jordan Cronenweth.
  • A. Corrsin
    Corrsin is a surname most notably associated with Stanley Corrsin, an influential American fluid dynamicist known for his work on turbulence.
  • B. Calbraith
    Calbraith is the middle name of U.S. naval officer Matthew Calbraith Perry, known for opening Japan to Western trade in the mid-19th century.
  • C. Essenrode
    Essenrode is a small village in Lower Saxony, Germany, historically associated with the noble von Hardenberg family.
  • D. Gwathmey
    Gwathmey is the surname of Charles Gwathmey, a prominent American architect known for his influential modernist designs.
  • E. Yarrowitch
    Yarrowitch is a small rural locality in New South Wales, Australia, known for its agricultural landscape and proximity to national parks and natural attractions.
  • 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_69d6aa609f008190a294200aefcb7bd5 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d732f878648190be5e25c56a7511cf completed April 9, 2026, 5:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69de564748ac8190beaaea44bb2d95ed completed April 14, 2026, 2:59 p.m.
NEDg Description generation batch_69de5eae7ab88190a0c512cfe61e3458 completed April 14, 2026, 3:35 p.m.
NED2 Entity disambiguation (via description) batch_69de60907e1081908405b6d71adbd388 completed April 14, 2026, 3:43 p.m.
Created at: April 8, 2026, 9:17 p.m.