Triple

T18711561
Position Surface form Disambiguated ID Type / Status
Subject Seabiscuit E457525 entity
Predicate editor P1954 FINISHED
Object William Goldenberg 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: William Goldenberg | Statement: [Seabiscuit, editor, William Goldenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: William Goldenberg
Context triple: [Seabiscuit, editor, 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. Steven Goldmann
    Steven Goldmann was a Canadian music video and film director best known for his prolific work in country music videos during the 1990s and 2000s.
  • C. Martin Goldstein
    Martin Goldstein, nicknamed "Buggsy," was an American mobster and hitman associated with Murder, Inc. during the 1930s and 1940s.
  • D. George Goldner
    George Goldner was an influential American record executive and producer known for founding several prominent independent labels that helped shape early rock and roll, doo-wop, and Latin music.
  • E. Melvyn Goldstein
    Melvyn Goldstein is an American anthropologist and Tibetologist renowned for his extensive research and publications on Tibetan society, history, and language.
  • 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_69d8d392aad081909fe31aa03e6e97d1 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5671b34508190b6180f7d6ad50a58 completed April 19, 2026, 11:36 p.m.
Created at: April 10, 2026, 11:50 a.m.