Triple

T14707326
Position Surface form Disambiguated ID Type / Status
Subject Michael Scofield E345459 entity
Predicate spouse P13 FINISHED
Object Sara Tancredi E348465 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: Sara Tancredi | Statement: [Michael Scofield, spouse, Sara Tancredi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sara Tancredi
Context triple: [Michael Scofield, spouse, Sara Tancredi]
  • A. Sara Tancredi chosen
    Sara Tancredi is a compassionate prison doctor who becomes a crucial ally and love interest to Michael Scofield in the television series "Prison Break."
  • B. Sara Serraiocco
    Sara Serraiocco is an Italian actress known for her acclaimed film and television roles, including a prominent part in the sci-fi thriller series "Counterpart."
  • C. Mara Carfagna
    Mara Carfagna is an Italian politician and former television showgirl who has served as a prominent minister and parliamentarian in center-right governments.
  • D. Tharita Cesaroni
    Tharita Cesaroni is an Italian film producer and cinematographer known for her work behind the camera and for being married to actor Dermot Mulroney.
  • E. Sara Forestier
    Sara Forestier is a French actress and filmmaker known for her acclaimed performances in contemporary French cinema, including César Award–winning roles.
  • 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_69d822e4a8c08190a155df736bb7bc13 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb609965081908f654bcb9eaaa145 completed April 14, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe72a181708190816c391f6a5d06f0 completed May 8, 2026, 11:32 p.m.
Created at: April 10, 2026, 1:28 a.m.