Triple

T20517660
Position Surface form Disambiguated ID Type / Status
Subject Tom Bernard E503721 entity
Predicate sharesPositionWith P91972 FINISHED
Object Michael Barker 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: Michael Barker | Statement: [Tom Bernard, sharesPositionWith, Michael Barker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Barker
Context triple: [Tom Bernard, sharesPositionWith, Michael Barker]
  • A. Michael Barker chosen
    Michael Barker is an American film executive and co-president of Sony Pictures Classics, known for distributing acclaimed independent and arthouse films.
  • B. Michael Barker
    Michael Barker was a British Army officer and general who held senior command positions, including leadership roles within I Corps, during the early stages of the Second World War.
  • C. David Barker
    David Barker is a film editor known for his work on contemporary cinema, including the 2020 film "Shirley."
  • D. Andrew Barker
    Andrew Barker is a British electronic musician best known as a member of the influential Manchester acid house and techno group 808 State.
  • E. Martin Boddey
    Martin Boddey was a British character actor known for his frequent supporting roles in mid-20th-century films and television, often portraying authority figures such as policemen and officials.
  • 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_69e0b4b2aa788190ae9eb37c1d73b1f1 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e69f42db688190a3ccfba5601e8bf3 completed April 20, 2026, 9:48 p.m.
Created at: April 16, 2026, 11:36 a.m.