Triple

T5751497
Position Surface form Disambiguated ID Type / Status
Subject Scott Hipwell E126863 entity
Predicate hasRelationshipWith P2830 FINISHED
Object Megan Hipwell E180120 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: Megan Hipwell | Statement: [Scott Hipwell, hasRelationshipWith, Megan Hipwell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Megan Hipwell
Context triple: [Scott Hipwell, hasRelationshipWith, Megan Hipwell]
  • A. Megan Hipwell chosen
    Megan Hipwell is a troubled young woman whose mysterious disappearance drives the central suspense and emotional tension in the psychological thriller film "The Girl on the Train."
  • B. Megan Gill
    Megan Gill is a film editor best known for her work on major feature films, including the superhero movie "X-Men Origins: Wolverine."
  • C. Megan Holley
    Megan Holley is an American screenwriter best known for writing the indie dramedy film "Sunshine Cleaning."
  • D. Amanda Hopkinson
    Amanda Hopkinson is a British literary translator and academic known for translating major works of Spanish and Latin American literature into English.
  • E. Meghan McDermott
    Meghan McDermott is an American public relations and communications professional best known for her marriage to actor Theo Rossi.
  • 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_69c00832aedc81909899801b141fa3b4 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0288a0ea8819091ac6f965471ceee completed March 22, 2026, 5:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0bf9968d881908ef4065d1d13b2b8 completed March 23, 2026, 4:20 a.m.
Created at: March 22, 2026, 3:48 p.m.