Triple

T4102361
Position Surface form Disambiguated ID Type / Status
Subject Balfe E87969 entity
Predicate hasNotableBearer P458 FINISHED
Object Caitríona Balfe E149442 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: Caitríona Balfe | Statement: [Balfe, hasNotableBearer, Caitríona Balfe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Caitríona Balfe
Context triple: [Balfe, hasNotableBearer, Caitríona Balfe]
  • A. Caitriona Balfe chosen
    Caitriona Balfe is an Irish actress and former fashion model best known for her lead role as Claire Fraser in the television series "Outlander."
  • B. Gillian Murphy
    Gillian Murphy is a renowned American ballet dancer and longtime principal with American Ballet Theatre, celebrated for her powerful technique and dramatic artistry.
  • C. Lena Headey
    Lena Headey is an English actress best known for playing Cersei Lannister in the television series "Game of Thrones."
  • D. Tessa Menzies
    Tessa Menzies is a child of California politician and governor Gavin Newsom.
  • E. Nathalie Emmanuel
    Nathalie Emmanuel is a British actress best known for her roles as Missandei in "Game of Thrones" and Ramsey in the "Fast & Furious" film franchise.
  • 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_69aed94564cc8190a9c1457daedb6e7f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefd1012208190ab0980c661d6bc41 completed March 9, 2026, 5:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69b56b7a917c8190914a5ffe1297fdc8 completed March 14, 2026, 2:06 p.m.
Created at: March 9, 2026, 3:40 p.m.