Triple

T3884008
Position Surface form Disambiguated ID Type / Status
Subject How to Marry a Millionaire E92894 entity
Predicate cinematographyBy P1953 FINISHED
Object Joseph MacDonald E319655 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: Joseph MacDonald | Statement: [How to Marry a Millionaire, cinematographyBy, Joseph MacDonald]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joseph MacDonald
Context triple: [How to Marry a Millionaire, cinematographyBy, Joseph MacDonald]
  • A. Joseph MacDonald chosen
    Joseph MacDonald was an American cinematographer known for his work on numerous classic Hollywood films, particularly in the 1940s and 1950s.
  • B. Philip MacDonald
    Philip MacDonald was a British-born novelist and screenwriter best known for his crime and mystery fiction and his contributions to classic Hollywood films.
  • C. Charles MacDonald
    Charles MacDonald was a distinguished American World War II fighter ace and U.S. Army Air Forces officer known for his combat achievements in the Pacific Theater.
  • D. Walter Connolly
    Walter Connolly was an American character actor of the 1930s known for his comic and often blustery supporting roles in Hollywood films.
  • E. John Applegate
    John Applegate was a 19th-century American pioneer and explorer associated with the development of overland emigrant routes in the western United States.
  • 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_69aed9697de0819087c2559295ff3d12 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aeec9029908190a7b36a3827734db1 completed March 9, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5125bee048190ba7553797e9fd254 completed March 14, 2026, 7:46 a.m.
Created at: March 9, 2026, 3:20 p.m.