Triple

T15996516
Position Surface form Disambiguated ID Type / Status
Subject Robert M. Edsel E387979 entity
Predicate name P16 FINISHED
Object Robert M. Edsel E387979 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: Robert M. Edsel | Statement: [Robert M. Edsel, name, Robert M. Edsel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Robert M. Edsel
Context triple: [Robert M. Edsel, name, Robert M. Edsel]
  • A. Robert M. Edsel chosen
    Robert M. Edsel is an American author and historian best known for his works documenting the Monuments Men and the Allied efforts to protect and recover art during World War II.
  • B. Edgar M. Kahn
    Edgar M. Kahn was an American neurosurgeon and academic known for his contributions to the development of neurosurgical techniques and education in the mid-20th century.
  • C. Robert S. Taubman
    Robert S. Taubman is an American real estate executive best known for leading the Taubman Company, a major developer and operator of shopping malls.
  • D. Raymond F. Kravis
    Raymond F. Kravis was an American businessman and philanthropist whose support for the arts led to major cultural institutions bearing his name.
  • E. Irving Glassberg
    Irving Glassberg was a Polish-born American cinematographer known for his work on numerous Universal Pictures films in the 1940s and 1950s.
  • 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_69d86daa562c81908aacc179c0fe8fb5 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e157882ef0819081143e530bd6413c completed April 16, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffc3d79dec8190b02e003f93e5dad6 completed May 9, 2026, 11:31 p.m.
Created at: April 10, 2026, 4:55 a.m.