Triple

T18888259
Position Surface form Disambiguated ID Type / Status
Subject Travels with My Aunt E462013 entity
Predicate cinematographer P1953 FINISHED
Object Douglas Slocombe 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: Douglas Slocombe | Statement: [Travels with My Aunt, cinematographer, Douglas Slocombe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Douglas Slocombe
Context triple: [Travels with My Aunt, cinematographer, Douglas Slocombe]
  • A. Douglas Slocombe chosen
    Douglas Slocombe was a renowned British cinematographer celebrated for his work on numerous classic films, including major entries in the Indiana Jones series.
  • B. Jeffrey Stott
    Jeffrey Stott is a film producer best known for his work on the political comedy film "The American President."
  • C. Richard Sibson
    Richard Sibson is a distinguished geologist recognized for his influential work on fault mechanics and earthquake processes.
  • D. Andrew MacRitchie
    Andrew MacRitchie is a film editor known for his work on major feature films, including the James Bond movie "Die Another Day."
  • E. Bruce Fowle
    Bruce Fowle is an American architect and co-founder of the firm FXFOWLE (now FXCollaborative), known for his work on prominent sustainable and high-rise buildings in New York City.
  • 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_69d8dcfc3430819095ee6fc0eb4c06a5 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c478d8c481909291e7c471e5095a completed April 20, 2026, 6:15 a.m.
Created at: April 10, 2026, 11:58 a.m.