Triple

T12674654
Position Surface form Disambiguated ID Type / Status
Subject All This, and Heaven Too E302773 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: [All This, and Heaven Too, editedBy, Warren Low]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Warren Low
Context triple: [All This, and Heaven Too, 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. Russell Carr
    Russell Carr is a British automotive designer best known as the head of design at Lotus Cars, where he has shaped the brand’s modern sports car lineup.
  • E. John L. Lumley
    John L. Lumley was a prominent American fluid dynamicist known for his pioneering contributions to the understanding and modeling of turbulence.
  • 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_69d7bdee64a08190801c6d470aefd723 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961af991c8190b6079cb57e593b8f completed April 10, 2026, 8:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67c7527c4819096c49a12dcba3c1a completed May 2, 2026, 10:36 p.m.
Created at: April 9, 2026, 5:20 p.m.