Triple

T20092975
Position Surface form Disambiguated ID Type / Status
Subject Fred Kohlmar E496320 entity
Predicate name P16 FINISHED
Object Fred Kohlmar E496320 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: Fred Kohlmar | Statement: [Fred Kohlmar, name, Fred Kohlmar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fred Kohlmar
Context triple: [Fred Kohlmar, name, Fred Kohlmar]
  • A. Fred Kohlmar chosen
    Fred Kohlmar was an American film producer active during Hollywood's studio era, known for overseeing a variety of popular comedies and musicals.
  • B. Don Dannemann
    Don Dannemann is an American singer and guitarist best known as a founding member and lead vocalist of the 1960s pop band The Cyrkle, which had hits like "Red Rubber Ball" and "Turn-Down Day."
  • C. Edward Knoblauch
    Edward Knoblauch, better known as Edward Knoblock, was an American-born British playwright and novelist noted for works such as the play "Kismet."
  • D. William Diehl
    William Diehl was an American novelist best known for his gritty, suspenseful legal and crime thrillers.
  • E. Paul W. Kiefer
    Paul W. Kiefer was an American engineer and industrialist best known for his pioneering role in developing diesel-electric locomotive technology and helping shape modern railroad motive power.
  • 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_69da626eee3881909f3454986d4a6511 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66668db8881908c43b1deef9af1d3 completed April 20, 2026, 5:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a090ae8c1848190893d765e75f74225 completed May 17, 2026, 12:25 a.m.
Created at: April 11, 2026, 11:22 p.m.