Triple

T12358283
Position Surface form Disambiguated ID Type / Status
Subject A Very Harold & Kumar 3D Christmas E294666 entity
Predicate cinematographyBy P1953 FINISHED
Object Michael Barrett E104613 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: Michael Barrett | Statement: [A Very Harold & Kumar 3D Christmas, cinematographyBy, Michael Barrett]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Barrett
Context triple: [A Very Harold & Kumar 3D Christmas, cinematographyBy, Michael Barrett]
  • A. Michael Barrett chosen
    Michael Barrett is an American cinematographer known for his work on numerous feature films and television projects, including mainstream comedies and action movies.
  • B. Matthew Barrett
    Matthew Barrett is an Irish cardiologist best known as the long-term partner of former Taoiseach and current Tánaiste Leo Varadkar.
  • C. Craig Barrett
    Craig Barrett is an American business executive and engineer best known for serving as CEO and chairman of Intel Corporation.
  • D. Michael O’Rourke
    Michael O’Rourke is best known as the father of the late child actress Heather O’Rourke, who starred in the "Poltergeist" film series.
  • E. Michael O’Rourke
    Michael O’Rourke is an Irish media entrepreneur best known as a co-founder of the international sports television network Setanta Sports.
  • 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_69d6ab6d8a4081908636601e69ddf262 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f8e64dc81908c2242c68cd1b86e completed April 10, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f69b7e7454819099d89db93d0fc1ea completed May 3, 2026, 12:49 a.m.
Created at: April 8, 2026, 9:54 p.m.