Triple

T15994140
Position Surface form Disambiguated ID Type / Status
Subject Florence Maxim E387917 entity
Predicate familyName P18 FINISHED
Object Maxim E338749 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: Maxim | Statement: [Florence Maxim, familyName, Maxim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maxim
Context triple: [Florence Maxim, familyName, Maxim]
  • A. Maxim chosen
    Maxim is a masculine given name of Latin origin, commonly used in Slavic and other European countries.
  • B. Maxim Roy
    Maxim Roy is a Canadian actress known for her work in film and television, including prominent roles in series such as Shadowhunters and 19-2.
  • C. Mark Francois
    Mark Francois is a British Conservative politician and Member of Parliament known for his roles in defence-related ministerial posts and his prominent support for Brexit.
  • D. Maxwell Sheffield
    Maxwell Sheffield is a wealthy, widowed Broadway producer and father of three who becomes the employer and eventual love interest of Fran Fine in the sitcom "The Nanny."
  • E. Alexandre Rockwell
    Alexandre Rockwell is an American independent film director and screenwriter known for his offbeat, character-driven movies such as "In the Soup" and his segment in the anthology film "Four Rooms."
  • 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_69e15785fad48190af0556e7ddfd29c5 completed April 16, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffc3d5d72081908aa235c5ad9b5707 completed May 9, 2026, 11:31 p.m.
Created at: April 10, 2026, 4:55 a.m.