Triple

T3668809
Position Surface form Disambiguated ID Type / Status
Subject Troy (film) E77827 entity
Predicate editedBy P1954 FINISHED
Object Peter Honess E217891 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: Peter Honess | Statement: [Troy (film), editedBy, Peter Honess]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peter Honess
Context triple: [Troy (film), editedBy, Peter Honess]
  • A. Peter Honess chosen
    Peter Honess is a British film editor best known for his work on major Hollywood films, including the acclaimed neo-noir crime drama "L.A. Confidential."
  • B. Robert Hohman
    Robert Hohman is an American entrepreneur best known as the co-founder and former CEO of Glassdoor, a popular platform for anonymous employee reviews and salary information.
  • C. Joseph Weishaar
    Joseph Weishaar is an American architect and designer best known for winning the competition to create the National World War I Memorial in Washington, D.C.
  • D. Anthony Kilhoffer
    Anthony Kilhoffer is a Grammy-winning American record producer and audio engineer known for his extensive work with artists like Kanye West and other major hip-hop and pop acts.
  • E. H. Peter Hofstee
    H. Peter Hofstee is a computer engineer and microprocessor architect best known for his work on advanced processor designs, including contributions at Transmeta and IBM.
  • 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_69ad85e083008190b2e1b7085fe500bd completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc42997d88190bc765559bd7645fc completed March 8, 2026, 6:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4884e36108190a19887e81921fe32 completed March 13, 2026, 9:57 p.m.
Created at: March 8, 2026, 3:25 p.m.