Triple

T3018162
Position Surface form Disambiguated ID Type / Status
Subject Gorilla at Large E82387 entity
Predicate editor P1954 FINISHED
Object Hugh S. Fowler E690797 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: Hugh S. Fowler | Statement: [Gorilla at Large, editor, Hugh S. Fowler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hugh S. Fowler
Context triple: [Gorilla at Large, editor, Hugh S. Fowler]
  • A. Hugh S. Fowler chosen
    Hugh S. Fowler was an American film editor best known for his work on major Hollywood productions, including the Academy Award-winning editing of "Patton."
  • B. Donald W. Sherburne
    Donald W. Sherburne was an American philosopher and prominent interpreter of Alfred North Whitehead’s process philosophy.
  • C. Franklin H. Martin
    Franklin H. Martin was an American surgeon and medical leader best known for founding and guiding the development of the American College of Surgeons.
  • D. Edward F. Storey
    Edward F. Storey was a 19th-century Nevada figure, likely a pioneer or local leader, for whom Storey County was named.
  • E. Franklin M. Fisher
    Franklin M. Fisher was an influential American economist known for his work in econometrics, industrial organization, and antitrust economics, and for his long tenure as a professor at MIT.
  • 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_69ad8b1eb53481908c39bbcd1ec104b2 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9a90ea64819080620e60bbd6aa24 completed March 8, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce88013b58819098bb60188fee1465 completed April 2, 2026, 3:15 p.m.
Created at: March 8, 2026, 3 p.m.