Triple

T11666466
Position Surface form Disambiguated ID Type / Status
Subject Mame Dennis E277262 entity
Predicate fullName P16 FINISHED
Object Mame Dennis E277261 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: Mame Dennis | Statement: [Mame Dennis, fullName, Mame Dennis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mame Dennis
Context triple: [Mame Dennis, fullName, Mame Dennis]
  • A. Mame Dennis chosen
    Mame Dennis is the flamboyant, free-spirited socialite aunt who serves as the central character in Patrick Dennis’s novel “Auntie Mame” and its stage and film adaptations.
  • B. Marge Loggia
    Marge Loggia is the wife of the late American actor and director Robert Loggia.
  • C. Margalo Gillmore
    Margalo Gillmore was an English-born American stage and film actress known for her sophisticated supporting roles in Broadway productions and classic Hollywood films of the mid-20th century.
  • D. Dixie Dwyer
    Dixie Dwyer is the fictional jazz cornetist and rising movie star portrayed by Richard Gere in the 1984 crime-drama film "The Cotton Club."
  • E. Doris Dowling
    Doris Dowling was an American film and television actress best known for her roles in classic 1940s noir and drama films.
  • 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_69d6aafd0a448190b44da30af8c6c519 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a43f438081909da476294a057c38 completed April 10, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef13b36ae4819096e6dfca23a69250 completed April 27, 2026, 7:43 a.m.
Created at: April 8, 2026, 9:39 p.m.