Triple

T11994962
Position Surface form Disambiguated ID Type / Status
Subject The Patsy E285504 entity
Predicate castMember P1668 FINISHED
Object Hedda Hopper E457009 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: Hedda Hopper | Statement: [The Patsy, castMember, Hedda Hopper]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hedda Hopper
Context triple: [The Patsy, castMember, Hedda Hopper]
  • A. Hedda Hopper chosen
    Hedda Hopper was a prominent American gossip columnist and former actress, notorious for her influential and often fearsome Hollywood gossip column during the mid-20th century.
  • B. Louella Parsons
    Louella Parsons was a powerful American gossip columnist and film critic who became one of early Hollywood’s most influential media figures.
  • C. Dorothy Kilgallen
    Dorothy Kilgallen was an American journalist and television personality best known as a sharp-witted newspaper columnist and longtime panelist on the game show "What's My Line?".
  • D. Marguerite Lauer
    Marguerite Lauer was the wife of renowned French Egyptologist Jean-Philippe Lauer.
  • E. Louella
    Louella is a feminine given name of English origin, often considered a combination of "Louise" and "Ella."
  • 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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903b211688190bfe6dd15c3f96d2f completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f47273e1088190b899071baff1375a completed May 1, 2026, 9:29 a.m.
Created at: April 8, 2026, 9:46 p.m.