Triple

T9995037
Position Surface form Disambiguated ID Type / Status
Subject Jaimie Alexander E197180 entity
Predicate spouse P13 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: [Jaimie Alexander, spouse, Peter Facinelli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peter Facinelli
Context triple: [Jaimie Alexander, spouse, 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. 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.
  • C. Brett Cullen
    Brett Cullen is an American actor known for his numerous film and television roles, including playing Thomas Wayne in the 2019 film "Joker."
  • D. Mario Adorf
    Mario Adorf is a renowned German-Swiss actor celebrated for his prolific film and television career across European cinema since the mid-20th century.
  • E. Gian Maria Volonté
    Gian Maria Volonté was an acclaimed Italian actor best known for his intense, politically charged performances and memorable villain roles in classic Spaghetti Westerns.
  • 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_69ca82f3b61c81908ecc2c1c96dbc2e4 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdcb99ac74819091f20816478ea375 completed April 2, 2026, 1:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69d26a2bc4f081909595afcc2c862eda completed April 5, 2026, 1:56 p.m.
Created at: March 30, 2026, 8:50 p.m.