Triple

T22092511
Position Surface form Disambiguated ID Type / Status
Subject Grease Live E545944 entity
Predicate stars P1956 FINISHED
Object Ana Gasteyer NE NERFINISHED

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: Ana Gasteyer | Statement: [Grease Live, stars, Ana Gasteyer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ana Gasteyer
Context triple: [Grease Live, stars, Ana Gasteyer]
  • A. Ana Gasteyer chosen
    Ana Gasteyer is an American actress and comedian best known for her work on "Saturday Night Live" and roles in films and television, including the cult teen comedy "Mean Girls."
  • B. Sabine Ganz
    Sabine Ganz is known as the spouse of the late Swiss actor Bruno Ganz, acclaimed for his roles in European cinema and theater.
  • C. Annette Kurschus
    Annette Kurschus is a German Protestant theologian and bishop who has served as a leading figure in the Evangelical Church in Germany.
  • D. Lissy Gerhardt
    Lissy Gerhardt is a fictional character known primarily as the daughter of Marine Gunnery Sergeant Mack Gerhardt in the military drama series "Over There."
  • E. Catherine Spaak
    Catherine Spaak was a French-Italian actress, singer, and television presenter best known for her prominent roles in 1960s Italian cinema and later work on Italian TV.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e36d03c8190a83a1ba802b7231b completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f128e6b1d881909bf0f4a52199354c completed April 28, 2026, 9:38 p.m.
Created at: April 16, 2026, 8:29 p.m.