Triple

T18260928
Position Surface form Disambiguated ID Type / Status
Subject Frank Drebin E437350 entity
Predicate worksWith P398 FINISHED
Object Ed Hocken NE NERFINISHED

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: Ed Hocken | Statement: [Frank Drebin, worksWith, Ed Hocken]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ed Hocken
Context triple: [Frank Drebin, worksWith, Ed Hocken]
  • A. Ed Hocken chosen
    Ed Hocken is a bumbling yet loyal police detective and sidekick to Lt. Frank Drebin in the slapstick comedy Naked Gun film series.
  • B. Bob Houghton
    Bob Houghton is an English football manager best known for his influential tactical innovations in the 1970s, including leading Malmö FF to the 1979 European Cup final.
  • C. Bob Huke
    Bob Huke was a British cinematographer known for his work on mid-20th-century films, including the 1962 war drama "The War Lover."
  • D. Cal Henderson
    Cal Henderson is a British software engineer and entrepreneur best known as the co-founder and CTO of the workplace communication platform Slack.
  • E. Gary Holton
    Gary Holton was an English actor and singer best known for playing the lovable rogue Wayne in the television series "Auf Wiedersehen, Pet."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b913351c8190932b6a426de04b41 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4ff7591b4819083f2b29d60298747 completed April 19, 2026, 4:14 p.m.
Created at: April 10, 2026, 10:34 a.m.