Triple

T15099445
Position Surface form Disambiguated ID Type / Status
Subject Charity Hope Valentine E360622 entity
Predicate relationshipTypeWithOscarLindquist P114501 FINISHED
Object romantic interest 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 interest | Statement: [Charity Hope Valentine, relationshipTypeWithOscarLindquist, romantic interest]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithOscarLindquist
Context triple: [Charity Hope Valentine, relationshipTypeWithOscarLindquist, romantic interest]
  • A. relationshipToStanley
    Indicates the specific type of personal or social relationship an entity has with Stanley.
  • B. Lincoln Lewis
    Indicates a relationship or association involving the entity or name "Lincoln Lewis," such as authorship, participation, or attribution in a given context.
  • C. relationshipToLoretta Castorini
    Indicates the specific familial, romantic, or social connection that an entity has to Loretta Castorini.
  • D. John Thornton Kirkland
    Indicates a naming relationship where the label or identifier "John Thornton Kirkland" is assigned to a specific individual.
  • E. relationshipTypeWithStephanie Ramzinski chosen
    Indicates the specific nature or category of relationship that an entity has with Stephanie Ramzinski.
  • F. None of above.

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_69d85a035aa88190b52a139d3a1b7b6d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0054f00388190a5123d9f4a869b96 completed April 15, 2026, 9:38 p.m.
PD Predicate disambiguation batch_69deb9645b9c8190a5712456dbd78029 completed April 14, 2026, 10:02 p.m.
Created at: April 10, 2026, 3:04 a.m.