Triple

T14879303
Position Surface form Disambiguated ID Type / Status
Subject Craig T. Nelson as Hayden Fox E349954 entity
Predicate relationshipTypeWithChristineArmstrong P116172 FINISHED
Object romantic partner LITERAL 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: romantic partner | Statement: [Craig T. Nelson as Hayden Fox, relationshipTypeWithChristineArmstrong, romantic partner]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithChristineArmstrong
Context triple: [Craig T. Nelson as Hayden Fox, relationshipTypeWithChristineArmstrong, romantic partner]
  • A. relationshipTypeWithStephanie Ramzinski
    Indicates the specific nature or category of relationship that an entity has with Stephanie Ramzinski.
  • B. relationshipTypeWithLizzieEustace
    Indicates the specific nature or category of relationship that an entity has with Lizzie Eustace.
  • C. relationshipTypeWithJulie d’Étange
    Indicates the specific nature or category of the relationship that an entity has with Julie d’Étange.
  • D. relationshipTypeWith Alicia Johns
    Indicates the specific type or nature of the relationship that an entity has with Alicia Johns.
  • E. relationshipTypeWithRobertAngier
    Indicates the specific nature or category of relationship that an entity has with Robert Angier.
  • F. None of above. chosen

Provenance (4 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_69d822ee4f408190b6ac3b2fa434f0df completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded5e622388190b2bf91cd10b9821d completed April 15, 2026, 12:03 a.m.
PD Predicate disambiguation batch_69de8c1a2bcc81908f914e2e2ced65eb completed April 14, 2026, 6:48 p.m.
PDg Predicate description generation batch_69de8f4c76e481909c0aa8d1a978e8d5 completed April 14, 2026, 7:02 p.m.
Created at: April 10, 2026, 1:55 a.m.