Triple

T7266933
Position Surface form Disambiguated ID Type / Status
Subject Lana Turner E160998 entity
Predicate name P16 FINISHED
Object Lana Turner E160998 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: Lana Turner | Statement: [Lana Turner, name, Lana Turner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lana Turner
Context triple: [Lana Turner, name, Lana Turner]
  • A. Lana Turner chosen
    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.
  • B. Joan Crawford
    Joan Crawford was a legendary American film actress and Hollywood star whose career spanned from the silent era to the 1970s, earning her an Academy Award and enduring icon status.
  • C. 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.
  • D. Linda Christian
    Linda Christian was a Mexican-born Hollywood actress best known as the first on-screen "Bond girl" in the 1954 television adaptation of Casino Royale.
  • E. Jean Arthur
    Jean Arthur was a celebrated American film actress of the 1930s and 1940s, best known for her distinctive husky voice and leading roles in classic screwball comedies and Frank Capra 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_69c6885181008190b419040e22939c7c completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eae7b2108190a6910f6655669db5 completed March 27, 2026, 8:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8342a44a08190abee47cc7482c757 completed March 28, 2026, 8:03 p.m.
Created at: March 27, 2026, 2:58 p.m.