Triple

T18079845
Position Surface form Disambiguated ID Type / Status
Subject Julian Fuego Thicke E432657 entity
Predicate hasRelative P367 FINISHED
Object Paula Patton 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: Paula Patton | Statement: [Julian Fuego Thicke, hasRelative, Paula Patton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paula Patton
Context triple: [Julian Fuego Thicke, hasRelative, Paula Patton]
  • A. Paula Patton chosen
    Paula Patton is an American actress known for her roles in films such as "Precious," "Mission: Impossible – Ghost Protocol," and various romantic comedies and dramas.
  • B. Emily Browning
    Emily Browning is an Australian actress known for her roles in films such as "A Series of Unfortunate Events," "Sucker Punch," and "Sleeping Beauty."
  • C. Erika Christensen
    Erika Christensen is an American actress known for her roles in films like "Traffic" and "Flightplan" and the television series "Parenthood."
  • D. Jessica Biel
    Jessica Biel is an American actress and producer known for her roles in the TV series "7th Heaven" and films such as "The Texas Chainsaw Massacre" and "The Illusionist."
  • E. Julie Hayden
    Julie Hayden was an American short story writer and journalist known for her acclaimed collection "The Lists of the Past" and her work at The New Yorker.
  • 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_69d8b907d05c819083cc3bd6021089e6 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4d9f81ff08190b7465e3c5568aa59 completed April 19, 2026, 1:34 p.m.
Created at: April 10, 2026, 10:27 a.m.