Triple

T3955701
Position Surface form Disambiguated ID Type / Status
Subject Zero Dark Thirty E84972 entity
Predicate editedBy P1954 FINISHED
Object William Goldenberg E156782 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: William Goldenberg | Statement: [Zero Dark Thirty, editedBy, William Goldenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: William Goldenberg
Context triple: [Zero Dark Thirty, editedBy, William Goldenberg]
  • A. William Goldenberg chosen
    William Goldenberg is an American film editor known for his work on numerous acclaimed movies, including several collaborations with directors like Michael Mann and Ben Affleck.
  • B. Johnny Goldstein
    Johnny Goldstein is an Israeli music producer and songwriter known for his work on international pop and hip-hop tracks.
  • C. Art Goldberg
    Art Goldberg was a prominent activist and organizer associated with the 1960s Free Speech Movement at the University of California, Berkeley.
  • D. Frank Goldberg
    Frank Goldberg is a businessman best known for owning the former American Basketball Association team the San Diego Sails.
  • E. Mort Goldman
    Mort Goldman is a neurotic, bespectacled Jewish pharmacist and recurring comic relief character on the animated television series Family Guy.
  • 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_69aed934fbfc8190847068e4546de963 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef93f3ad48190b96b98b4aecd6030 completed March 9, 2026, 4:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd7f58290881908c7622616a829c75 completed March 20, 2026, 5:09 p.m.
Created at: March 9, 2026, 3:30 p.m.