Triple

T7501030
Position Surface form Disambiguated ID Type / Status
Subject Floridita bar E177259 entity
Predicate notablePatron P29285 FINISHED
Object Ava Gardner E32485 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: Ava Gardner | Statement: [Floridita bar, notablePatron, Ava Gardner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ava Gardner
Context triple: [Floridita bar, notablePatron, Ava Gardner]
  • A. Ava Gardner chosen
    Ava Gardner was a celebrated American film actress and Hollywood icon of the 1940s and 1950s, renowned for her beauty, charisma, and roles in classics such as "The Killers" and "Mogambo."
  • B. Gloria Grahame
    Gloria Grahame was an American film actress known for her sultry screen presence and acclaimed roles in classic Hollywood films noir and dramas of the 1940s and 1950s.
  • C. Lizabeth Scott
    Lizabeth Scott was an American film actress known for her sultry voice and frequent roles as a femme fatale in 1940s and 1950s film noir.
  • D. Lauren Bacall
    Lauren Bacall was an iconic American film and stage actress known for her sultry voice, striking looks, and classic roles in 1940s Hollywood noir films.
  • E. Lana Turner
    Lana Turner was a glamorous American film actress and iconic Hollywood star of the 1940s and 1950s, renowned for her dramatic roles and enduring screen presence.
  • 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_69c69f2696688190915a8458f2398211 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f59aabb8819085bdbe9c793d5b8b completed March 27, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c968c9a1a48190b6ea5bb08ff745af completed March 29, 2026, 6 p.m.
Created at: March 27, 2026, 3:44 p.m.