Triple

T14822191
Position Surface form Disambiguated ID Type / Status
Subject Lola Ray Facinelli E348477 entity
Predicate father P120 FINISHED
Object Peter Facinelli E69016 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: Peter Facinelli | Statement: [Lola Ray Facinelli, father, Peter Facinelli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peter Facinelli
Context triple: [Lola Ray Facinelli, father, Peter Facinelli]
  • A. Peter Facinelli chosen
    Peter Facinelli is an American actor best known for playing Dr. Carlisle Cullen in the Twilight film series.
  • B. Gian Luca Gregori
    Gian Luca Gregori is an Italian academic who serves as the rector of Marche Polytechnic University.
  • C. Danielo Giovanni Travanti
    Danielo Giovanni Travanti, better known as Daniel J. Travanti, is an American actor best known for his Emmy-winning role as Captain Frank Furillo on the television series "Hill Street Blues."
  • D. Stefano Accorsi
    Stefano Accorsi is an Italian actor known for his prominent roles in contemporary Italian cinema and television, including crime dramas and character-driven films.
  • E. Giancarlo Giannini
    Giancarlo Giannini is an acclaimed Italian actor and voice actor known for his intense performances in European cinema and international films, as well as for dubbing prominent Hollywood actors into Italian.
  • 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_69d822eb8f588190bf53445e730a934f completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decfe64328819083ce42704cf0602d completed April 14, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69feb7d279708190a54a56c0b80be10a completed May 9, 2026, 4:28 a.m.
Created at: April 10, 2026, 1:51 a.m.