Triple

T13236360
Position Surface form Disambiguated ID Type / Status
Subject Come September E315155 entity
Predicate starring P1507 FINISHED
Object Sandra Dee E254597 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: Sandra Dee | Statement: [Come September, starring, Sandra Dee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sandra Dee
Context triple: [Come September, starring, Sandra Dee]
  • A. Sandra Dee chosen
    Sandra Dee was an American actress and teen idol of the late 1950s and 1960s, best known for films like "Gidget" and "A Summer Place."
  • B. Diana Lynn
    Diana Lynn was an American film and television actress best known for her work in 1940s and 1950s Hollywood comedies and dramas.
  • C. Pat Farrah
    Pat Farrah is an American retail executive best known as a co-founder of The Home Depot and a key architect of the big-box home improvement store concept.
  • D. Debbie Rowe
    Debbie Rowe is an American nurse best known as Michael Jackson’s ex-wife and the mother of two of his children.
  • E. Cheryl White
    Cheryl White is a supporting character in the sports drama film "McFarland, USA," depicted as part of the community surrounding the high school cross-country team.
  • 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_69d806b1072881909e46bd212259c5f0 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98d56da008190af55da3a9e7ffd4d completed April 10, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7305c5f8081908bbe19f2a644acc5 completed May 3, 2026, 11:24 a.m.
Created at: April 9, 2026, 9:22 p.m.