Triple

T13498726
Position Surface form Disambiguated ID Type / Status
Subject Rhonda Fleming E320827 entity
Predicate spouse P13 FINISHED
Object Ted Mann E502610 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: Ted Mann | Statement: [Rhonda Fleming, spouse, Ted Mann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ted Mann
Context triple: [Rhonda Fleming, spouse, Ted Mann]
  • A. Ted Mann chosen
    Ted Mann was an American film exhibitor and businessman best known for owning the Mann Theatres chain and the historic Grauman’s Chinese Theatre in Hollywood.
  • B. Tom Mann
    Tom Mann was a prominent British trade unionist and socialist leader known for his key role in the New Unionism movement and early labor organizing in the late 19th and early 20th centuries.
  • C. Robert Mann
    Robert Mann was a 19th-century American man best known as the son of influential education reformer Horace Mann.
  • D. Arthur Mann
    Arthur Mann is a music industry figure known for co-founding the influential independent record label Rykodisc.
  • E. Brian Singerman
    Brian Singerman is an American venture capitalist and prominent partner at Founders Fund, known for investing in high-growth technology startups.
  • 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_69d807629d6c8190998f1b9bb12d2ed0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaf4fab688190bdc746985b0c7338 completed April 12, 2026, 2:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75485af6c8190a43ccab5449f5014 completed May 3, 2026, 1:58 p.m.
Created at: April 9, 2026, 9:43 p.m.