Triple

T19868224
Position Surface form Disambiguated ID Type / Status
Subject Legally Blonde E477445 entity
Predicate character P662 FINISHED
Object Paulette Bonafonté 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: Paulette Bonafonté | Statement: [Legally Blonde, character, Paulette Bonafonté]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paulette Bonafonté
Context triple: [Legally Blonde, character, Paulette Bonafonté]
  • A. Paulette Bonafonté chosen
    Paulette Bonafonté is a lovable, quirky Boston hairstylist and Elle Woods’s supportive friend in the musical and film versions of Legally Blonde.
  • B. Annette Roque
    Annette Roque is a Dutch former model and equestrian who gained public attention as the ex-wife of American television journalist Matt Lauer.
  • C. Janine Perreau
    Janine Perreau is an American former child actress who appeared in several films and television shows during the 1950s and 1960s.
  • D. Paulette Morisset
    Paulette Morisset is known primarily as the daughter of André Morisset.
  • E. Marjorie Estiano
    Marjorie Estiano is a Brazilian actress and singer acclaimed for her powerful television performances and international recognition.
  • 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_69d8e51e7d948190aedbcd6c30361c39 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e658a168288190a2fbb735d1fd30a8 completed April 20, 2026, 4:47 p.m.
Created at: April 10, 2026, 1:51 p.m.