Triple

T14552172
Position Surface form Disambiguated ID Type / Status
Subject David Duchovny E341443 entity
Predicate spouse P13 FINISHED
Object Téa Leoni E289044 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: Téa Leoni | Statement: [David Duchovny, spouse, Téa Leoni]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Téa Leoni
Context triple: [David Duchovny, spouse, Téa Leoni]
  • A. Téa Leoni chosen
    Téa Leoni is an American actress and producer best known for her leading roles in film and television, including the political drama series "Madam Secretary."
  • B. Elizabeth Berkley
    Elizabeth Berkley is an American actress best known for her roles in the TV series "Saved by the Bell" and the film "Showgirls."
  • C. Annabella Sciorra
    Annabella Sciorra is an American actress known for her work in film and television, including acclaimed roles in movies like "Jungle Fever" and the TV series "The Sopranos."
  • D. Laura Kugler
    Laura Kugler was the wife of Victor Kugler, one of the helpers who hid Anne Frank and her family during World War II.
  • E. Allison Hunt
    Allison Hunt is a fictional character in the television series "Grey's Anatomy," known primarily as the deceased sister of trauma surgeon Owen Hunt, whose death deeply affects his storyline.
  • 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_69d822db9c8481908213ceb39585f792 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb2ee34208190bf040a513767c958 completed April 14, 2026, 9:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69fef883f2b88190807d9157e8d45e3c completed May 9, 2026, 9:04 a.m.
Created at: April 10, 2026, 1:23 a.m.