Triple

T10226241
Position Surface form Disambiguated ID Type / Status
Subject True Crime E243210 entity
Predicate cinematographyBy P1953 FINISHED
Object Jack N. Green E234194 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: Jack N. Green | Statement: [True Crime, cinematographyBy, Jack N. Green]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jack N. Green
Context triple: [True Crime, cinematographyBy, Jack N. Green]
  • A. Jack N. Green chosen
    Jack N. Green is an American cinematographer best known for his longtime collaboration with Clint Eastwood on films such as "Unforgiven" and "The Bridges of Madison County."
  • B. Jack Green
    Jack Green is an entrepreneur best known as a founder of the major American insurance company Progressive Corporation.
  • C. Chuck Green
    Chuck Green was an influential American tap dancer and innovator whose rhythmic style and artistry helped shape modern tap and inspired later stars like Savion Glover.
  • D. Daniel Green
    Daniel Green is a music producer known for his work on the track "Paradise."
  • E. Angus T. Jones
    Angus T. Jones is an American actor best known for his role as Jake Harper on the television sitcom "Two and a Half Men."
  • 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_69d381b0f97c819085c9b45799a5fb7c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d1f9cf6c81909a6b9e9b9d0a79fe completed April 7, 2026, 9:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f71fb4048190a36f1fe499729332 completed April 9, 2026, 12:47 a.m.
Created at: April 6, 2026, 11:17 a.m.