Triple

T7049526
Position Surface form Disambiguated ID Type / Status
Subject Paris When It Sizzles E163728 entity
Predicate editedBy P1954 FINISHED
Object Warren Low E280717 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: Warren Low | Statement: [Paris When It Sizzles, editedBy, Warren Low]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Warren Low
Context triple: [Paris When It Sizzles, editedBy, Warren Low]
  • A. Warren Low chosen
    Warren Low was a Hollywood film editor known for his work on numerous studio productions during the mid-20th century.
  • B. Herbert R. O'Conor
    Herbert R. O'Conor was an American Democratic politician who served as governor of Maryland and later as a U.S. senator in the mid-20th century.
  • C. Paul W. Airey
    Paul W. Airey was a United States Air Force noncommissioned officer who became a pioneering enlisted leader and the inaugural Chief Master Sergeant of the Air Force.
  • D. John L. Lumley
    John L. Lumley was a prominent American fluid dynamicist known for his pioneering contributions to the understanding and modeling of turbulence.
  • E. Walter Bunning
    Walter Bunning was a prominent Australian architect and urban planner known for his influential postwar designs and contributions to modernist architecture in Australia.
  • 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_69c6885f598c8190b6b6495c59d8d962 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6e24d5e8c8190b37e56107e6da8ab completed March 27, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7888bba9c8190b6414b56e5588ec0 completed March 28, 2026, 7:51 a.m.
Created at: March 27, 2026, 2:37 p.m.