Triple

T14329627
Position Surface form Disambiguated ID Type / Status
Subject Cheaper by the Dozen 2 E355310 entity
Predicate starring P1507 FINISHED
Object Liliana Mumy E949980 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: Liliana Mumy | Statement: [Cheaper by the Dozen 2, starring, Liliana Mumy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Liliana Mumy
Context triple: [Cheaper by the Dozen 2, starring, Liliana Mumy]
  • A. Liliana Mumy chosen
    Liliana Mumy is an American actress and voice actress known for her roles in family films and animated television series such as "Cheaper by the Dozen" and "The Loud House."
  • B. Irina Malandina
    Irina Malandina is a former Russian flight attendant best known as the ex-wife of billionaire businessman and former Chelsea F.C. owner Roman Abramovich.
  • C. Miriam Svet
    Miriam Svet was the wife of American film producer and studio executive Dore Schary.
  • D. Ludmila Mikaël
    Ludmila Mikaël is a French actress known for her work in film, theatre, and television since the late 1960s.
  • E. Sofia Rosinsky
    Sofia Rosinsky is an American actress best known for her starring role in the science fiction television series "Paper Girls."
  • 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_69d8278fa2108190bc0d0e7939c1eb03 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8c1def0081908f03cda8e84d20c0 completed April 14, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c3d20688190973e37ca38b4afe0 completed May 8, 2026, 2:36 a.m.
Created at: April 10, 2026, 1:13 a.m.