Triple

T10793937
Position Surface form Disambiguated ID Type / Status
Subject Jeff Cronenweth E254654 entity
Predicate name P16 FINISHED
Object Jeff Cronenweth E254654 NE FINISHED

How this triple was built (2 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: Jeff Cronenweth | Statement: [Jeff Cronenweth, name, Jeff Cronenweth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jeff Cronenweth
Context triple: [Jeff Cronenweth, name, Jeff Cronenweth]
  • A. Jeff Cronenweth chosen
    Jeff Cronenweth is an American cinematographer known for his stylish, atmospheric work on films such as "The Social Network" and collaborations with director David Fincher.
  • B. James DeMonaco
    James DeMonaco is an American filmmaker and screenwriter best known for creating and writing the dystopian horror franchise "The Purge."
  • C. Steven DeRose
    Steven DeRose is a computer scientist and linguist known for his influential work in digital text encoding and markup languages, particularly in the development and standardization of XML-related technologies.
  • D. John Seitz
    John Seitz was an American cinematographer renowned for his influential work in classic Hollywood cinema, particularly in film noir and science fiction.
  • E. Kevin Reynolds
    Kevin Reynolds is an American film director best known for helming movies such as "Robin Hood: Prince of Thieves" and "Waterworld."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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.
Created at: April 8, 2026, 9:17 p.m.