Triple

T4356463
Position Surface form Disambiguated ID Type / Status
Subject Sergeant York E98158 entity
Predicate screenwriter P2831 FINISHED
Object Howard Koch E134926 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: Howard Koch | Statement: [Sergeant York, screenwriter, Howard Koch]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Howard Koch
Context triple: [Sergeant York, screenwriter, Howard Koch]
  • A. Howard Koch chosen
    Howard Koch was an American screenwriter best known for co-writing the classic film "Casablanca" and for his work in radio and Hollywood during the mid-20th century.
  • B. Harry Waxman
    Harry Waxman was a British cinematographer known for his work on numerous mid-20th-century films, including the 1960 adaptation of "Swiss Family Robinson."
  • C. Ralph Berkowitz
    Ralph Berkowitz was an American pianist, accompanist, and arts administrator known for his influential work in classical music performance and education.
  • D. Charles Fleischmann
    Charles Fleischmann was a 19th-century entrepreneur and co-founder of the Fleischmann Yeast Company, which revolutionized commercial baking in the United States.
  • E. Ralph Guggenheim
    Ralph Guggenheim is an American film producer best known for his work at Pixar, where he helped pioneer computer-animated feature filmmaking.
  • 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_69b3454965f881908c41190bb22f0e4b completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b351c68a588190ba14a298afacb1dc completed March 12, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5dbb9b9988190adf8a84de3582ab6 completed March 14, 2026, 10:05 p.m.
Created at: March 12, 2026, 11:16 p.m.